Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Takeaways:
- Organizational thinking must change: Value-added data management practices must be considered and included as a vital part of your business strategy.
- Walk before you run with data focused initiatives: Understand and implement necessary data management prerequisites as a foundation, then build upon that foundation.
- There are no silver bullets: Tools alone are not the answer. Specifying business requirements, business practices and data governance are almost always more important.
Effective BI Portal Design Patterns to Drive High User EngagementDATAVERSITY
A well-designed BI Portal can be transformational by dramatically boosting user engagement with analytics. Providing a highly tailored user experience helps users cut through the clutter in the reporting environment and engage with the right analytics to drive good decision-making.
This webinar will outline the top drivers for poor BI engagement and will present portal page design patterns that:
1. Streamline the experience of working across many dashboards
2. Enable efficient top-down exploration of KPIs across multiple dashboards
3. Deliver context required for data literacy together with analytics
Specific examples will be shared for each design pattern to illustrate how the Portal page design is effective in creating a delightful user experience that delivers high BI user engagement.
Data-Ed Online Webinar: Data Governance StrategiesDATAVERSITY
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
Takeaways:
Understanding why data governance can be tricky for most organizations
Steps for improving data governance within your organization
Guiding principles & lessons learned
Understanding foundational data governance concepts based on the DAMA DMBOK
Enterprise Data World: Data Governance - The Four Critical Success FactorsDATAVERSITY
Let’s face it, developing and implementing an Enterprise Data Governance program can be very frustrating. Issues can pop up quite unexpectedly. Support ebbs and flows for seemingly illogical reasons. And, acceptance and adoption seem to be hit or miss. So, how can practitioners ensure their program will be as successful as possible?
This webinar is designed to help practitioners understand the Four Critical Success Factors necessary for developing and sustaining an effective Data Governance program, as identified by Joy Medved based on her 20+ years as an international data consultant. Joy will provide an overview of the Four Critical Success Factors, as well as share Common Program Barriers she has experienced that lead to success breakdown. Joy will also help practitioners learn how to identify if one or more of these critical success factors is plaguing your program, and which barriers might be at fault. Rounding out the topic, Joy will share her Key Program Components, designed to help ensure successful Data Governance development and implementation.
Some of the topics discussed in this webinar include:
The Four Critical Success Factors for developing and implementing a DG program
Common Program Barriers that may be hampering your ability to drive a successful program
How to identify which barriers might be plaguing your program efforts
Key Program Components to help ensure a successful DG program
The Chief Data Officer's Agenda: What a CDO Needs to Know about Data QualityDATAVERSITY
Data is the ultimate cross-enterprise asset. Data and information flow throughout an organization and require both business and IT expertise to manage them effectively. The same data is available for multiple users, unlike physical products that once sold to a buyer cannot be resold to the next customer who walks through the door or places an online order. These properties create unique challenges for the CDO chartered to oversee the data management organization. The purpose of any data management work is to ensure high quality, trusted data and information, yet data quality is a profession within itself. Join us to learn what a CDO needs to know about data quality:
The relationship between data quality, governance, and other data management functions
Options for structuring within your organization
The difference between data quality programs and projects
What a CDO can do to help both data quality programs and projects succeed
Pitfalls and pro-tips for effective and transparent Business Intelligence too...Data Con LA
Data Con LA 2020
Description
*Identify key players plus team functions
*Unpack user requirements to answer business critical service or support needs
*Question everything to know what you don't know
*Build Business Intelligence Tools and Services governance for change management roadmap
*What this means for you
Speaker
Jason Medina, Global Decision, Data Scientist
Data Leadership - Stop Talking About Data and Start Making an Impact!DATAVERSITY
<!-- wp:paragraph -->
<p>For any organization to be successful, whatever we do with data must connect to meaningful business improvements—and those must be measured. If current data efforts lack results or accountability, then Data Leadership is our answer.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>But Data Leadership isn’t really about the data at all. What makes Data Leadership so powerful is its ability to completely transform organizations. Going beyond traditional data management and governance, Data Leadership builds momentum and delivers the change we’ve long known our businesses need. Data Leadership helps us overcome the lingering data challenges our legacy approaches never will.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>This webinar will cover the key concepts of Data Leadership, and what anybody can do to start making a bigger impact for their teams and businesses. Whether your role today is large or small, Data Leadership will be essential to your future data success! </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Key Learnings Include:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>What Data Value really is, and why creating it is the goal of everything we do with data</li><li>Introduction to the Data Leadership Framework</li><li>Why Data Leadership is fundamentally about balance</li><li>How to immediately start making a Data Leadership impact in your organization</li></ul>
<!-- /wp:list -->
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
Much like project team management and home improvement, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance is the process by which an organization delegates responsibility and exercises control over mission-critical data assets. In practice, though, Data Governance directs how all other Data Management functions are performed, meaning that much of your Data Management strategy’s capacity to function at all depends on your effectiveness in governing its implementation. Understanding these aspects of governance is necessary to eliminate the ambiguity that often surrounds effective Data Management and stewardship programs, since the goal of governance is to manage the data that supports organizational strategy.
This webinar will:
Illustrate what Data Governance functions are required for effective Data Management, how they fit with other Data Management disciplines, and why Data Governance can be tricky for many organizations
Help you develop a detailed vocabulary and set of narratives to facilitate understanding of your business objectives and imperatives that demand governance
Provide direction for selling Data Governance to organizational management as a specifically motivated initiative
Discuss foundational Data Governance concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Effective BI Portal Design Patterns to Drive High User EngagementDATAVERSITY
A well-designed BI Portal can be transformational by dramatically boosting user engagement with analytics. Providing a highly tailored user experience helps users cut through the clutter in the reporting environment and engage with the right analytics to drive good decision-making.
This webinar will outline the top drivers for poor BI engagement and will present portal page design patterns that:
1. Streamline the experience of working across many dashboards
2. Enable efficient top-down exploration of KPIs across multiple dashboards
3. Deliver context required for data literacy together with analytics
Specific examples will be shared for each design pattern to illustrate how the Portal page design is effective in creating a delightful user experience that delivers high BI user engagement.
Data-Ed Online Webinar: Data Governance StrategiesDATAVERSITY
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
Takeaways:
Understanding why data governance can be tricky for most organizations
Steps for improving data governance within your organization
Guiding principles & lessons learned
Understanding foundational data governance concepts based on the DAMA DMBOK
Enterprise Data World: Data Governance - The Four Critical Success FactorsDATAVERSITY
Let’s face it, developing and implementing an Enterprise Data Governance program can be very frustrating. Issues can pop up quite unexpectedly. Support ebbs and flows for seemingly illogical reasons. And, acceptance and adoption seem to be hit or miss. So, how can practitioners ensure their program will be as successful as possible?
This webinar is designed to help practitioners understand the Four Critical Success Factors necessary for developing and sustaining an effective Data Governance program, as identified by Joy Medved based on her 20+ years as an international data consultant. Joy will provide an overview of the Four Critical Success Factors, as well as share Common Program Barriers she has experienced that lead to success breakdown. Joy will also help practitioners learn how to identify if one or more of these critical success factors is plaguing your program, and which barriers might be at fault. Rounding out the topic, Joy will share her Key Program Components, designed to help ensure successful Data Governance development and implementation.
Some of the topics discussed in this webinar include:
The Four Critical Success Factors for developing and implementing a DG program
Common Program Barriers that may be hampering your ability to drive a successful program
How to identify which barriers might be plaguing your program efforts
Key Program Components to help ensure a successful DG program
The Chief Data Officer's Agenda: What a CDO Needs to Know about Data QualityDATAVERSITY
Data is the ultimate cross-enterprise asset. Data and information flow throughout an organization and require both business and IT expertise to manage them effectively. The same data is available for multiple users, unlike physical products that once sold to a buyer cannot be resold to the next customer who walks through the door or places an online order. These properties create unique challenges for the CDO chartered to oversee the data management organization. The purpose of any data management work is to ensure high quality, trusted data and information, yet data quality is a profession within itself. Join us to learn what a CDO needs to know about data quality:
The relationship between data quality, governance, and other data management functions
Options for structuring within your organization
The difference between data quality programs and projects
What a CDO can do to help both data quality programs and projects succeed
Pitfalls and pro-tips for effective and transparent Business Intelligence too...Data Con LA
Data Con LA 2020
Description
*Identify key players plus team functions
*Unpack user requirements to answer business critical service or support needs
*Question everything to know what you don't know
*Build Business Intelligence Tools and Services governance for change management roadmap
*What this means for you
Speaker
Jason Medina, Global Decision, Data Scientist
Data Leadership - Stop Talking About Data and Start Making an Impact!DATAVERSITY
<!-- wp:paragraph -->
<p>For any organization to be successful, whatever we do with data must connect to meaningful business improvements—and those must be measured. If current data efforts lack results or accountability, then Data Leadership is our answer.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>But Data Leadership isn’t really about the data at all. What makes Data Leadership so powerful is its ability to completely transform organizations. Going beyond traditional data management and governance, Data Leadership builds momentum and delivers the change we’ve long known our businesses need. Data Leadership helps us overcome the lingering data challenges our legacy approaches never will.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>This webinar will cover the key concepts of Data Leadership, and what anybody can do to start making a bigger impact for their teams and businesses. Whether your role today is large or small, Data Leadership will be essential to your future data success! </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Key Learnings Include:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>What Data Value really is, and why creating it is the goal of everything we do with data</li><li>Introduction to the Data Leadership Framework</li><li>Why Data Leadership is fundamentally about balance</li><li>How to immediately start making a Data Leadership impact in your organization</li></ul>
<!-- /wp:list -->
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
Much like project team management and home improvement, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance is the process by which an organization delegates responsibility and exercises control over mission-critical data assets. In practice, though, Data Governance directs how all other Data Management functions are performed, meaning that much of your Data Management strategy’s capacity to function at all depends on your effectiveness in governing its implementation. Understanding these aspects of governance is necessary to eliminate the ambiguity that often surrounds effective Data Management and stewardship programs, since the goal of governance is to manage the data that supports organizational strategy.
This webinar will:
Illustrate what Data Governance functions are required for effective Data Management, how they fit with other Data Management disciplines, and why Data Governance can be tricky for many organizations
Help you develop a detailed vocabulary and set of narratives to facilitate understanding of your business objectives and imperatives that demand governance
Provide direction for selling Data Governance to organizational management as a specifically motivated initiative
Discuss foundational Data Governance concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Social media and relationship development for salesEconsultancy
Econsultancy Director Peter Abraham's presentation on the topic of social media and relationship development for sales. (originally presented at Chicago Booth University School of Business)
RWDG Slides: The Stewardship Approach to Data GovernanceDATAVERSITY
Everybody in the organization is a data steward if they are held accountable for their relationship to data. Understanding who does what with the data is an easy way to recognize who your data stewards are. The data stewards are the people your Data Governance program will rely on.
Join Bob Seiner for this month’s webinar, where when he will focus on the role that lies at the heart of any approach to a Data Governance program. The first challenge of many programs is to recognize the stewards and assist them in seeing themselves in that important role.
In this webinar, Bob will discuss:
• Why everybody is a data steward
• The stewards’ impact on the complexity of your program
• How to leverage existing data responsibility
• Engaging stewards based on their relationship to data
• How to follow a Stewardship Approach
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
DAS Webinar: Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY® survey on Emerging Trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
DataEd Slides: Data Management Best PracticesDATAVERSITY
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This approach combines the DM BoK and the CMMI/DMM, permitting organizations with the opportunity to benefit from the best of both. The approach permits organizations to understand current Data Management practices, strengths to leverage, and remediation opportunities. In a nutshell, it describes what must be done at the programmatic level to achieve better data use.
Metadata is hotter than ever, according a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
DAS Slides: Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as Customers, Products, Vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar provides practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/
While many Digital Transformation initiatives are focused on improving the customer experience, often too little attention is paid to the customer-facing operational decisions that impact customers every day. To get the most from your Digital Transformation efforts, your customers’ experience and the decisions that impact it cannot be ignored.
ADV Slides: Organizational Change Management in Becoming an Analytic Organiza...DATAVERSITY
The disparity between expecting change and managing it – the “change gap” – is growing at an unprecedented pace. This has put many information management shops into traction as they initiate large, complex projects needed to stay competitive.
Information management professionals and business leaders must concern themselves with the organization’s acceptance of these efforts. To be successful in achieving the larger enterprise goals, these initiatives must transform the organization. However, it takes more than wishful thinking to bridge the gap.
The complexities of engaging behavioral and enterprise transformation are too often underestimated at great peril, because the “soft stuff” is truly hard. In this webinar, William McKnight will outline:
• The change readiness activities that focus on identifying and addressing people risks
• The tasks that will mobilize and align leaders to create outstanding business value
• The strategies to manage stakeholders, ensure change readiness, and address the organizational implications
• The methodologies to train the workforce as required to fully embrace and utilize the system
The global pandemic returned digital transformation to the spotlight. The lockdown put every digital business model to the test. Some organizations proved agile and resilient, but most were sent back to the drawing board to reconstruct their digital and analytic foundations.
In response, the modern C-Suite is now being tightly knit into one digital whole, connected by a web of data and analytics.
These slides--based on the webinar from leading IT research firm Enterprise Management Associates (EMA)-- outline the priorities of digital transformation in the modern C-Suite.
Big Challenges in Data Modeling: Modeling MetadataDATAVERSITY
We invite you to join us in this monthly DATAVERSITY webinar series, “Big Challenges with Data Modeling” hosted by Karen Lopez. Join Karen and guest expert panelists each month to discuss their experiences in breaking through these specific data modeling challenges. Hear from experts in the field on how and where they came across these challenges and what resolution they found. Join them in the end for the Q&A portion to ask your own questions on the challenge topic of the month.
DAS Slides: Data Quality Best PracticesDATAVERSITY
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
DataEd Slides: Getting Started with Data StewardshipDATAVERSITY
In order to find value in your organization’s data assets, heroic Data Stewards are tasked with saving the day—every single day! These heroes adhere to a Data Governance framework, and work to ensure that data is captured right the first time, validated through automated means, and integrated into business processes. Whether it’s data profiling or in-depth root cause analysis, Data Stewards can be counted on to ensure the organization’s mission-critical data is reliable. In this webinar, we will approach this framework and punctuate important facets of a Data Steward’s role.
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
Takeaways:
Understanding why data governance can be tricky for most organizations
Steps for improving data governance within your organization
Guiding principles & lessons learned
Understanding foundational data governance concepts based on the DAMA DMBOK
Social media and relationship development for salesEconsultancy
Econsultancy Director Peter Abraham's presentation on the topic of social media and relationship development for sales. (originally presented at Chicago Booth University School of Business)
RWDG Slides: The Stewardship Approach to Data GovernanceDATAVERSITY
Everybody in the organization is a data steward if they are held accountable for their relationship to data. Understanding who does what with the data is an easy way to recognize who your data stewards are. The data stewards are the people your Data Governance program will rely on.
Join Bob Seiner for this month’s webinar, where when he will focus on the role that lies at the heart of any approach to a Data Governance program. The first challenge of many programs is to recognize the stewards and assist them in seeing themselves in that important role.
In this webinar, Bob will discuss:
• Why everybody is a data steward
• The stewards’ impact on the complexity of your program
• How to leverage existing data responsibility
• Engaging stewards based on their relationship to data
• How to follow a Stewardship Approach
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
DAS Webinar: Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY® survey on Emerging Trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
DataEd Slides: Data Management Best PracticesDATAVERSITY
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This approach combines the DM BoK and the CMMI/DMM, permitting organizations with the opportunity to benefit from the best of both. The approach permits organizations to understand current Data Management practices, strengths to leverage, and remediation opportunities. In a nutshell, it describes what must be done at the programmatic level to achieve better data use.
Metadata is hotter than ever, according a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
DAS Slides: Master Data Management – Aligning Data, Process, and GovernanceDATAVERSITY
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as Customers, Products, Vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous – from real-time operational integration to data warehousing and analytic reporting. This webinar provides practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Enterprise Architecture vs. Data ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as they relate to data and its business impact across the organization. Join us for a discussion on how data architecture is a key component of an overall enterprise architecture for enhanced business value and success.
Many data professionals struggle with the ability to demonstrate tangible returns on data management investments. In a webinar that is designed to appeal to both business and IT attendees, your presenter Dr. Peter Aiken will describe multiple types of value produced through data-centric development and management practices. One of our examples, the healthcare space, offers the unique opportunity to demonstrate additional types of return on investment or value outcomes, namely returns in the form of lives saved through increased rates of Bone Marrow Donor matches. In addition to metrics around increasing revenues or decreasing costs, i.e. investments that directly impact an organization’s financial position, these additional statistics of lives saved can be used to justify data management and quality initiatives.
Check out more of our webinars here: http://www.datablueprint.com/resource-center/
While many Digital Transformation initiatives are focused on improving the customer experience, often too little attention is paid to the customer-facing operational decisions that impact customers every day. To get the most from your Digital Transformation efforts, your customers’ experience and the decisions that impact it cannot be ignored.
ADV Slides: Organizational Change Management in Becoming an Analytic Organiza...DATAVERSITY
The disparity between expecting change and managing it – the “change gap” – is growing at an unprecedented pace. This has put many information management shops into traction as they initiate large, complex projects needed to stay competitive.
Information management professionals and business leaders must concern themselves with the organization’s acceptance of these efforts. To be successful in achieving the larger enterprise goals, these initiatives must transform the organization. However, it takes more than wishful thinking to bridge the gap.
The complexities of engaging behavioral and enterprise transformation are too often underestimated at great peril, because the “soft stuff” is truly hard. In this webinar, William McKnight will outline:
• The change readiness activities that focus on identifying and addressing people risks
• The tasks that will mobilize and align leaders to create outstanding business value
• The strategies to manage stakeholders, ensure change readiness, and address the organizational implications
• The methodologies to train the workforce as required to fully embrace and utilize the system
The global pandemic returned digital transformation to the spotlight. The lockdown put every digital business model to the test. Some organizations proved agile and resilient, but most were sent back to the drawing board to reconstruct their digital and analytic foundations.
In response, the modern C-Suite is now being tightly knit into one digital whole, connected by a web of data and analytics.
These slides--based on the webinar from leading IT research firm Enterprise Management Associates (EMA)-- outline the priorities of digital transformation in the modern C-Suite.
Big Challenges in Data Modeling: Modeling MetadataDATAVERSITY
We invite you to join us in this monthly DATAVERSITY webinar series, “Big Challenges with Data Modeling” hosted by Karen Lopez. Join Karen and guest expert panelists each month to discuss their experiences in breaking through these specific data modeling challenges. Hear from experts in the field on how and where they came across these challenges and what resolution they found. Join them in the end for the Q&A portion to ask your own questions on the challenge topic of the month.
DAS Slides: Data Quality Best PracticesDATAVERSITY
Tackling Data Quality problems requires more than a series of tactical, one-off improvement projects. By their nature, many Data Quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process, and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control Data Quality issues in your organization.
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to today’s organization, and provide insights into building successful business strategies for metadata adoption & use.
DataEd Slides: Getting Started with Data StewardshipDATAVERSITY
In order to find value in your organization’s data assets, heroic Data Stewards are tasked with saving the day—every single day! These heroes adhere to a Data Governance framework, and work to ensure that data is captured right the first time, validated through automated means, and integrated into business processes. Whether it’s data profiling or in-depth root cause analysis, Data Stewards can be counted on to ensure the organization’s mission-critical data is reliable. In this webinar, we will approach this framework and punctuate important facets of a Data Steward’s role.
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
Takeaways:
Understanding why data governance can be tricky for most organizations
Steps for improving data governance within your organization
Guiding principles & lessons learned
Understanding foundational data governance concepts based on the DAMA DMBOK
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
Is your company having trouble driving more revenue from current clients?
Are you losing your current clients to competitors?
Watch this presentation to learn how to build B2B strategic account teams to generate 3X more revenue and profit than originally believed, within a short period of time.
RWDG Slides: Apply Data Governance to Agile EffortsDATAVERSITY
Data Governance Programs and Agile Data Projects are known to conflict when it comes to how the information and data is managed. Senior leadership has come to expect both the formal governance of data and data projects to be delivered quickly and effectively. These two requirements continue to cause problems.
Bob Seiner will discuss how to govern data during Agile projects during this month’s installment of the RWDG webinar series. It is inevitable that governance and Agile need to work together and complement each discipline’s intended results. Bob will share several considerations for bringing the two together.
During this webinar Bob will discuss:
- Looking for common ground to stand on
- The data goals of an Agile effort
- The Agile goals of a Data Governance program
- Bridging the gap and building understanding
- Steps to apply governance to Agile efforts
Competitive dimensions - strategic management - Manu Melwin Joymanumelwin
According to Porter, two competitive dimensions are the keys to business-level strategy.
The first dimension is a firm’s source of competitive advantage.
The second dimension is firms’ scope of operations.
This presentation takes you through the theory and setting up a Balanced Scorecard for your organisation. This presentation also discusses the linkages between the Balanced Scorecard and the value chain (Optimise-GB, creating operational efficiencies)
If you are having writers block when generating / creating ideas for you, your business, career path, investment opportunity then this “creating and evaluating ideas” tool is for you. It is simple in design and should help you generate ideas freely without judgement or criticism to get your creative juices flowing. Once you have identified many creative ideas, this tool will help you evaluate them, one by one, against your objectives.
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Takeaways:
Organizational thinking must change: Value-added data management practices must be considered and included as a vital part of your business strategy.
Walk before you run with data focused initiatives: Understand and implement necessary data management prerequisites as a foundation, then build upon that foundation.
There are no silver bullets: Tools alone are not the answer. Specifying business requirements, business practices and data governance are almost always more important.
Building a Complete View Across the Customer Experience on Oracle BICSShiv Bharti
Many organizations today are using a Modern Business Intelligence Platform or Big Data to eliminate Customer Blind Spots. When most firms refer to Big Data, they are not necessarily using “BIG” data, the term is used interchangeably with Analytics by most of our Customers.
Organizations today are increasingly relying on Data to make strategic decisions. Marketing Departments are using Predictive analytics to identify the Prospects or segments that will give their firms the most “lift” and thus highest ROI.
What are Customer Blind Spots?
Gaps in your view of the customer relationship across time
No formal social media listening data
Lack of cross-device identity
Inability for organizations to deliver personalized customer experiences
Inability to apply predictive analytics to customer behavior to optimize products and services
What are the Challenges to eliminate blind spots?
Disparate Data sources
Multiple Sources of the truth
Growth in Data Volumes
Data Migration Challenges
Fundamental Considerations for a Customer 360 project
Customer 360 project should focus on making substantial improvements in 5 key areas: Improve data quality, create Linkages across our various systems, centralize disparate information, transform the data to enable action and insights, and streamline the manner in which data is accessed and available.
Each pillar contains a stream of work broken into parallel paths to accelerate the rollout and adoption of the platform.
If you’re attending @Oracleopenworld (#oow16) and are considering a project to build a Customer 360-degree view by eliminating Customer Blind spots, please join us for our session to learn more on this subject including a customer case study. We look forward to a great session and stimulating conversations.
Building a Complete View Across the Customer Experience on Oracle BI Cloud Service [CON3730]
Monday, Sep 19, 4:15 p.m. – 5:00 p.m. | Moscone West – 2006
Anil Kaul, CEO and Co-Founder, AbsolutData delivered a session on institutionalizing Big Data analytics for organizations, at the Big Data Innovation Summit, London on 1st May, 2013.
AbsolutData is a global leader in applying analytics to drive sales and increase profits for its customers. AbsolutData has built strong expertise and traction with Fortune 1000 companies across 40 countries. We specialize in big data, high end business analytics, predictive modeling, research, reporting, social media analytics and data management services. AbsolutData delivers world class analytics solutions by combining their expertise in industry domains, analytical techniques and sophisticated tools.
Visit us here : www.absolutdata.com
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
Check out more webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
The data governance function exercises authority and control over the management of your mission critical assets and guides how all other data management functions are performed. When selling data governance to organizational management, it is useful to concentrate on the specifics that motivate the initiative. This means developing a specific vocabulary and set of narratives to facilitate understanding of your organizational business concepts. This webinar provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these aspects is a necessary pre-requisite to eliminate the ambiguity that often surrounds initial discussions and implement effective data governance and stewardship programs that manage data in support of organizational strategy.
Find more of our Data-Ed webinars here: http://www.datablueprint.com/resource-center/webinar-schedule/
Building a Data Strategy Your C-Suite Will SupportReid Colson
Being a data leader in any industry is an advantage that creates measurable financial benefits. Many studies have shown this – I’ve seen them from Bain, McKinsey, MIT and more. Since most firms are measured on profit, getting good at making data driven decisions is a key to being competitive. You can't get there without a plan. That is where a data strategy comes in.
In speaking with ~300 firms who indicated that their organizations were effective in using data and analytics, McKinsey found that construction of a data strategy was the number one contributing factor to their success. Being good at using data to drive decisions creates a meaningful profit advantage and those who are leaders indicated that the number one driver of their success was their data strategy.
This presentation will cover what a data strategy is, how to construct one, and how to get buy in from your executive team. The author is a former Fortune 500 Chief Data Officer and has held senior data roles at Capital One and Markel.
Here are a few helpful links for your data journey:
Free Data Investment ROI Template:
https://www.udig.com/digging-in/roi-calculator-for-it-projects/
Real world data use cases:
https://www.udig.com/our-work/?category=data
Contact Me:
https://www.udig.com/contact/
The Business Value of Metadata for Data GovernanceRoland Bullivant
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change.
Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Data Architecture Strategies: Building an Enterprise Data Strategy – Where to...DATAVERSITY
The majority of successful organizations in today’s economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate “quick wins” for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Selling MDM to Leadership: Defining the WhyProfisee
It's one of the hardest things to do prior to beginning an MDM initiative, but understanding why you need MDM from a business point of view is critical to ensure the success of the project.
About UCI Applied Innovation:
UCI Applied Innovation is a dynamic, innovative central platform for the UCI campus, entrepreneurs, inventors, the business community and investors to collaborate and move UCI research from lab to market.
About the Cove @ UCI:
To accelerate collaboration by better connecting innovation partners in Orange County, UCI Applied Innovation created the Cove, a physical, state-of-the-art hub for entrepreneurs to gather and navigate the resources available both on and off campus. The Cove is headquarters for UCI Applied Innovation, as well as houses several ecosystem partners including incubators, accelerators, angel investors, venture capitalists, mentors and legal experts.
Follow us on social media:
Facebook: @UCICove
Twitter: @UCICove
Instagram: @UCICove
LinkedIn: @UCIAppliedInnovation
For more information:
cove@uci.edu
http://innovation.uci.edu/
Ironside's VP of Strategy & Innovation, Greg Bonnette, delivered a presentation on "How to Build a Winning Strategy for Data & Analytics" to provide a framework for data-driven decision making.
Data Driven Culture with Slalom's Director of AnalyticsPromotable
Everyone wants to capture the benefits of big data by making better data driven decision. We are inundated by analytical tools that deliver "insights" and process information quickly.
Although often overlooked, creating a data driven culture is as important as finding the right tools to make data driven decisions. Organizations who skip this foundational element often find their investment in Data tools and personal don't yield the benefits that becoming Data Driven is supposed to unlock.
In this talk you'll learn about why creating a Data Driven culture is vital to every organization and the starting point for ensuring your data strategy generates strong impact and ROI.
Takeaways:
What is a data driven culture? Where does it start?
What happens when you implement tools (tableau, power BI, Machine Learning, etc) without first having a data driven culture
Stages of a Data Driven Culture?
How to get started?
Your Instructor: Kevin Chapin is the Practice Director for Data and Analytics at Slalom Consulting.
To see the full talk, click here: https://www.youtube.com/watch?v=7xNLgiK31Is
Architecture, Products, and Total Cost of Ownership of the Leading Machine Le...DATAVERSITY
Organizations today need a broad set of enterprise data cloud services with key data functionality to modernize applications and utilize machine learning. They need a comprehensive platform designed to address multi-faceted needs by offering multi-function data management and analytics to solve the enterprise’s most pressing data and analytic challenges in a streamlined fashion.
In this research-based session, I’ll discuss what the components are in multiple modern enterprise analytics stacks (i.e., dedicated compute, storage, data integration, streaming, etc.) and focus on total cost of ownership.
A complete machine learning infrastructure cost for the first modern use case at a midsize to large enterprise will be anywhere from $3 million to $22 million. Get this data point as you take the next steps on your journey into the highest spend and return item for most companies in the next several years.
Data at the Speed of Business with Data Mastering and GovernanceDATAVERSITY
Do you ever wonder how data-driven organizations fuel analytics, improve customer experience, and accelerate business productivity? They are successful by governing and mastering data effectively so they can get trusted data to those who need it faster. Efficient data discovery, mastering and democratization is critical for swiftly linking accurate data with business consumers. When business teams can quickly and easily locate, interpret, trust, and apply data assets to support sound business judgment, it takes less time to see value.
Join data mastering and data governance experts from Informatica—plus a real-world organization empowering trusted data for analytics—for a lively panel discussion. You’ll hear more about how a single cloud-native approach can help global businesses in any economy create more value—faster, more reliably, and with more confidence—by making data management and governance easier to implement.
What is data literacy? Which organizations, and which workers in those organizations, need to be data-literate? There are seemingly hundreds of definitions of data literacy, along with almost as many opinions about how to achieve it.
In a broader perspective, companies must consider whether data literacy is an isolated goal or one component of a broader learning strategy to address skill deficits. How does data literacy compare to other types of skills or “literacy” such as business acumen?
This session will position data literacy in the context of other worker skills as a framework for understanding how and where it fits and how to advocate for its importance.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace – from digital transformation, to marketing, to customer centricity, to population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Uncover how your business can save money and find new revenue streams.
Driving profitability is a top priority for companies globally, especially in uncertain economic times. It's imperative that companies reimagine growth strategies and improve process efficiencies to help cut costs and drive revenue – but how?
By leveraging data-driven strategies layered with artificial intelligence, companies can achieve untapped potential and help their businesses save money and drive profitability.
In this webinar, you'll learn:
- How your company can leverage data and AI to reduce spending and costs
- Ways you can monetize data and AI and uncover new growth strategies
- How different companies have implemented these strategies to achieve cost optimization benefits
Data Catalogs Are the Answer – What is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
Data Catalogs Are the Answer – What Is the Question?DATAVERSITY
Organizations with governed metadata made available through their data catalog can answer questions their people have about the organization’s data. These organizations get more value from their data, protect their data better, gain improved ROI from data-centric projects and programs, and have more confidence in their most strategic data.
Join Bob Seiner for this lively webinar where he will talk about the value of a data catalog and how to build the use of the catalog into your stewards’ daily routines. Bob will share how the tool must be positioned for success and viewed as a must-have resource that is a steppingstone and catalyst to governed data across the organization.
In this webinar, Bob will focus on:
-Selecting the appropriate metadata to govern
-The business and technical value of a data catalog
-Building the catalog into people’s routines
-Positioning the data catalog for success
-Questions the data catalog can answer
Because every organization produces and propagates data as part of their day-to-day operations, data trends are becoming more and more important in the mainstream business world’s consciousness. For many organizations in various industries, though, comprehension of this development begins and ends with buzzwords: “Big Data,” “NoSQL,” “Data Scientist,” and so on. Few realize that all solutions to their business problems, regardless of platform or relevant technology, rely to a critical extent on the data model supporting them. As such, data modeling is not an optional task for an organization’s data effort, but rather a vital activity that facilitates the solutions driving your business. Since quality engineering/architecture work products do not happen accidentally, the more your organization depends on automation, the more important the data models driving the engineering and architecture activities of your organization. This webinar illustrates data modeling as a key activity upon which so much technology and business investment depends.
Specific learning objectives include:
- Understanding what types of challenges require data modeling to be part of the solution
- How automation requires standardization on derivable via data modeling techniques
- Why only a working partnership between data and the business can produce useful outcomes
Analytics play a critical role in supporting strategic business initiatives. Despite the obvious value to analytic professionals of providing the analytics for these initiatives, many executives question the economic return of analytics as well as data lakes, machine learning, master data management, and the like.
Technology professionals need to calculate and present business value in terms business executives can understand. Unfortunately, most IT professionals lack the knowledge required to develop comprehensive cost-benefit analyses and return on investment (ROI) measurements.
This session provides a framework to help technology professionals research, measure, and present the economic value of a proposed or existing analytics initiative, no matter the form that the business benefit arises. The session will provide practical advice about how to calculate ROI and the formulas, and how to collect the necessary information.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Enterprise data literacy. A worthy objective? Certainly! A realistic goal? That remains to be seen. As companies consider investing in data literacy education, questions arise about its value and purpose. While the destination – having a data-fluent workforce – is attractive, we wonder how (and if) we can get there.
Kicking off this webinar series, we begin with a panel discussion to explore the landscape of literacy, including expert positions and results from focus groups:
- why it matters,
- what it means,
- what gets in the way,
- who needs it (and how much they need),
- what companies believe it will accomplish.
In this engaging discussion about literacy, we will set the stage for future webinars to answer specific questions and feature successful literacy efforts.
The Data Trifecta – Privacy, Security & Governance Race from Reactivity to Re...DATAVERSITY
Change is hard, especially in response to negative stimuli or what is perceived as negative stimuli. So organizations need to reframe how they think about data privacy, security and governance, treating them as value centers to 1) ensure enterprise data can flow where it needs to, 2) prevent – not just react – to internal and external threats, and 3) comply with data privacy and security regulations.
Working together, these roles can accelerate faster access to approved, relevant and higher quality data – and that means more successful use cases, faster speed to insights, and better business outcomes. However, both new information and tools are required to make the shift from defense to offense, reducing data drama while increasing its value.
Join us for this panel discussion with experts in these fields as they discuss:
- Recent research about where data privacy, security and governance stand
- The most valuable enterprise data use cases
- The common obstacles to data value creation
- New approaches to data privacy, security and governance
- Their advice on how to shift from a reactive to resilient mindset/culture/organization
You’ll be educated, entertained and inspired by this panel and their expertise in using the data trifecta to innovate more often, operate more efficiently, and differentiate more strategically.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Trends - A Look Backwards and ForwardsDATAVERSITY
As DATAVERSITY’s RWDG series hurdles into our 12th year, this webinar takes a quick look behind us, evaluates the present, and predicts the future of Data Governance. Based on webinar numbers, hot Data Governance topics have evolved over the years from policies and best practices, roles and tools, data catalogs and frameworks, to supporting data mesh and fabric, artificial intelligence, virtualization, literacy, and metadata governance.
Join Bob Seiner as he reflects on the past and what has and has not worked, while sharing examples of enterprise successes and struggles. In this webinar, Bob will challenge the audience to stay a step ahead by learning from the past and blazing a new trail into the future of Data Governance.
In this webinar, Bob will focus on:
- Data Governance’s past, present, and future
- How trials and tribulations evolve to success
- Leveraging lessons learned to improve productivity
- The great Data Governance tool explosion
- The future of Data Governance
Data Governance Trends and Best Practices To Implement TodayDATAVERSITY
Would you share your bank account information on social media? How about shouting your social security number on the New York City subway? We didn’t think so either – that’s why data governance is consistently top of mind.
In this webinar, we’ll discuss the common Cloud data governance best practices – and how to apply them today. Join us to uncover Google Cloud’s investment in data governance and learn practical and doable methods around key management and confidential computing. Hear real customer experiences and leave with insights that you can share with your team. Let’s get solving.
Topics that you will hear addressed in this webinar:
- Understanding the basics of Cloud Incident Response (IR) and anticipated data governance trends
- Best practices for key management and apply data governance to your day-to-day
- The next wave of Confidential Computing and how to get started, including a demo
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the enterprise mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and data architecture. William will kick off the fifth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Too often I hear the question “Can you help me with our data strategy?” Unfortunately, for most, this is the wrong request because it focuses on the least valuable component: the data strategy itself. A more useful request is: “Can you help me apply data strategically?” Yes, at early maturity phases the process of developing strategic thinking about data is more important than the actual product! Trying to write a good (must less perfect) data strategy on the first attempt is generally not productive –particularly given the widespread acceptance of Mike Tyson’s truism: “Everybody has a plan until they get punched in the face.” This program refocuses efforts on learning how to iteratively improve the way data is strategically applied. This will permit data-based strategy components to keep up with agile, evolving organizational strategies. It also contributes to three primary organizational data goals. Learn how to improve the following:
- Your organization’s data
- The way your people use data
- The way your people use data to achieve your organizational strategy
This will help in ways never imagined. Data are your sole non-depletable, non-degradable, durable strategic assets, and they are pervasively shared across every organizational area. Addressing existing challenges programmatically includes overcoming necessary but insufficient prerequisites and developing a disciplined, repeatable means of improving business objectives. This process (based on the theory of constraints) is where the strategic data work really occurs as organizations identify prioritized areas where better assets, literacy, and support (data strategy components) can help an organization better achieve specific strategic objectives. Then the process becomes lather, rinse, and repeat. Several complementary concepts are also covered, including:
- A cohesive argument for why data strategy is necessary for effective data governance
- An overview of prerequisites for effective strategic use of data strategy, as well as common pitfalls
- A repeatable process for identifying and removing data constraints
- The importance of balancing business operation and innovation
Who Should Own Data Governance – IT or Business?DATAVERSITY
The question is asked all the time: “What part of the organization should own your Data Governance program?” The typical answers are “the business” and “IT (information technology).” Another answer to that question is “Yes.” The program must be owned and reside somewhere in the organization. You may ask yourself if there is a correct answer to the question.
Join this new RWDG webinar with Bob Seiner where Bob will answer the question that is the title of this webinar. Determining ownership of Data Governance is a vital first step. Figuring out the appropriate part of the organization to manage the program is an important second step. This webinar will help you address these questions and more.
In this session Bob will share:
- What is meant by “the business” when it comes to owning Data Governance
- Why some people say that Data Governance in IT is destined to fail
- Examples of IT positioned Data Governance success
- Considerations for answering the question in your organization
- The final answer to the question of who should own Data Governance
It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:
- Their current Data Management practices
- Strengths that should be leveraged
- Remediation opportunities
MLOps – Applying DevOps to Competitive AdvantageDATAVERSITY
MLOps is a practice for collaboration between Data Science and operations to manage the production machine learning (ML) lifecycles. As an amalgamation of “machine learning” and “operations,” MLOps applies DevOps principles to ML delivery, enabling the delivery of ML-based innovation at scale to result in:
Faster time to market of ML-based solutions
More rapid rate of experimentation, driving innovation
Assurance of quality, trustworthiness, and ethical AI
MLOps is essential for scaling ML. Without it, enterprises risk struggling with costly overhead and stalled progress. Several vendors have emerged with offerings to support MLOps: the major offerings are Microsoft Azure ML and Google Vertex AI. We looked at these offerings from the perspective of enterprise features and time-to-value.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
1. Data-centric Strategy & Roadmap
Date:
February 11, 2014
Time:
2:00 PM ET
11:00 AM PT
Presenters: Peter Aiken,
Lewis Broome
1
Copyright 2014 by Data Blueprint
2. Commonly Asked Questions
1) Will I get copies of the slides
after the event?
2) Is this being recorded so I
can view it afterwards?
2
Copyright 2014 by Data Blueprint
3. Get Social with Us!
Live Twitter Feed
@datablueprint
@paiken
#dataed
Like Us
www.facebook.com/datablueprint
Join the Group
Data Management & Business Intelligence
3
Copyright 2014 by Data Blueprint
4. Building a Data-centric Strategy &
Roadmap
What needs to be done… avoiding a haphazard
approach
Presented by Peter Aiken, Ph.D. and Lewis Broome
5. Lewis Broome
• CEO Data Blueprint
• 20+ years in data
management
• Experienced leader driving
global solutions for
Fortune 100 companies
• Creatively disrupting the
approach to data
management
• Published in multiple
industry periodicals
Peter Aiken
• 30+ years DM
experience
• 9 books/
many articles
• Experienced with
500+ data
management
practices
• Multi-year
immersions: US DoD,
Nokia, Deutsche
Bank, Wells Fargo, &
Commonwealth of VA
5
Copyright 2014 by Data Blueprint
6. Building a Data-centric Strategy &
Roadmap
What needs to be done … avoiding a haphazard
approach
Presented by Peter Aiken, Ph.D. and Lewis Broome
Copyright 2014 by Data Blueprint
7. Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– An Example
• Measurement & Success Criteria
– An Overview
– An Example
• Developing a Solution to Address Needs
– Closing Foundational Gaps
– Solving for Specific Needs
• Developing a Roadmap and Plan
• Q&A
7
Copyright 2014 by Data Blueprint
8. Simon Sinek: How great leaders inspire action
WHY
HOW
“…it’s not what you do,
it’s why you do it”
WHAT
http://www.ted.com/talks/simon_sinek_how_great_leaders_inspire_action.html
8
Copyright 2014 by Data Blueprint
9. Summary: Enterprise Data Strategy Choices
Q4
Using data to create
strategic opportunities
Innovation
Q3
Both (Cash Cow)
Only 1 in 10 organizations has a
board approved data strategy!
Q1
Q2
Keeping the doors open
(little or no proactive data
management)
Increasing organizational
efficiencies/effectiveness
Improve Operations
9
Copyright 2014 by Data Blueprint
10. ‘Why’ a Data Strategy?
Data becoming inextricably linked to, and part of, the actual products &
services being sold
Customers see enhanced value in having relevant, accurate & meaningful information
combined with the products and services they purchase
Information is power in a competitive market place
Situational awareness (e.g. a 360º view) of your customers, suppliers, competition & operating
environment creates a competitive advantage that enables you to plan and react
Volume and velocity of data impacting operating models
Organizations are being put at greater operating and reputational risk because legacy business
processes and systems are straining under the requirements to process and understand everincreasing volumes and speed of data
Read more at my blog: http://www.datablueprint.com/winning-todays-information-economy-data-centric-business-strategy/
10
Copyright 2014 by Data Blueprint
11. Putting the Data Strategy Together
Get on the same
page with
business partners
Measure
Business Value
Develop a holistic
solution and
approach
Get a true understanding of your organization’s
competitive advantage and current business goals
Working with business leaders, managers and
operators, define specific opportunities to meet
the organizational goals
Collaborating with your business partners, define
the metrics that measure levels of success
Develop a comprehensive solution using people,
process, data and technology
Outline an achievable implementation plan in a
roadmap with timelines, milestones and level of
effort estimates
Note: For many organizations this requires a transformation in how they think and
operate – this is the greatest challenge in becoming a ‘data-driven’ organization
11
Copyright 2014 by Data Blueprint
12. Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– An Example
• Measurement & Success Criteria
– An Overview
– An Example
• Developing a Solution to Address Needs
– Closing Foundational Gaps
– Solving for Specific Business Needs
• Developing a Roadmap and Plan
• Q&A
12
Copyright 2014 by Data Blueprint
13. Understanding Your Company’s Competitive
Advantage
• Do you really know why your company has an
advantage over the competition?
– You may be surprised!
– Its not about being the best, its about being different
(counter intuitive)
– Its about deciding between a set of trade-offs
– Data strategy must align
• Frameworks for understanding competitive
advantage
–
–
–
–
–
Porter’s Five Forces
Porter’s Competitive Strategic Matrix
SWOT Analysis
PEST Analysis
Four Corners Analysis
13
Copyright 2014 by Data Blueprint
14. Porter’s Competitive Strategic Matrix
Product Differentiation: How specifically focused are your
products?
Cost: Are you
competing on cost?
How cost-sensitive is
your market?
Market Scope: Are you
focused on a narrow
market (i.e. niche) or a
broad market of
customers?
Lower Cost
Differentiation
Broad
Broad Overall Low-Cost
Leadership
Differentiation
Range of
Strategy
Strategy
Buyers
Blue Ocean
Brands
Narrow
Buyer
Segment
Focused
Low-Cost
Strategy
Focused
Differentiation
Strategy
Note: (Typically) Can’t be all things to all consumers –
where are you?
14
Copyright 2014 by Data Blueprint
15. Porter’s Competitive Strategic Matrix - Examples
Lower Cost
Differentiation
Broad
Range of
Buyers
Narrow
Buyer
Segment
15
Copyright 2014 by Data Blueprint
16. Porter’s Five Forces
Once you find your place in the four quadrants…What is your competitive
advantage?
Bargaining Power of Buyers: The degree
of leverage customers have over your
company
Bargaining Power of Suppliers: The
degree of leverage suppliers have over your
company
Threat of New Entrants: How hard is it for
new competition to enter the market?
Threat of Substitute Products: How easy
(or hard) is it for customers to switch to
alternative products?
Competitive Rivalry: How competitive is
the market place?
http://www.strategy-keys.com/michael-porter-five-forces-model.html
16
Copyright 2014 by Data Blueprint
17. An Example – The Automotive Industry
Once you find your place in the four quadrants….
•
What is your competitive advantage against those around you?
Lower Cost
Differentiation
Broad
Broad Overall Low-Cost
Leadership
Differentiation
Range of
Strategy
Strategy
Buyers
Blue Ocean
Brands
Narrow
Buyer
Segment
Focused
Low-Cost
Strategy
Focused
Differentiation
Strategy
17
Copyright 2014 by Data Blueprint
18. Applying the Five Forces
5 Forces
Porsche
Hyundai
Threat of New Entrants
Very Weak
Weak
Bargaining Power of Buyers
Moderate
Very Strong
Bargaining Power of Suppliers
Weak
Very Weak
Threat of Substitutes
Moderate
Strong
Competitive Rivalry
Moderate
Strong
Porsche
• Customer relationship data is critical. Develop individualized customer interactions
• High quality & efficient data processing to support R&D to further differentiate products
Hyundai
• Price-sensitive customers. Use strength over suppliers to maintain low COGS.
• Reduce non-value added to keep operational costs low by eliminating inefficiencies
created by poor data quality
18
Copyright 2014 by Data Blueprint
19. Data Value Generation Take-Away
Source: http://www.cioupdate.com/insights/article.php/3936706/The-4-Principles-of-a-Successful-Data-Strategy.htm
19
Copyright 2014 by Data Blueprint
20. Summary: Same Page with Your Business Partners
A Data Strategy must be Business Focused
• Understand the business fundamentals of your organization
• Develop a common language and shared perspective with your
business partners – enabling collaboration
• Identify specific business opportunities or areas of improvement
• Focus the data strategy solution on improving those
specific business needs
Next Step:
• Measuring business value of
making improvements:
• Metrics, Object of Measurement and Methods
20
Copyright 2014 by Data Blueprint
21. One of two choices
• Good business strategy
– Understand what it really is:
• Organizational strategy
• IT strategy
• Data strategy
• Got to figure out/improve the business strategy
– Analysis
– What changes would be seen
as useful/important?
– Plan to accomplishing
something useful …
21
Copyright 2014 by Data Blueprint
22. Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– An Example
• Measurement & Success Criteria
– An Overview
– An Example
• Developing a Solution to Address Needs
– Closing Foundational Gaps
– Solving for Specific Business Needs
• Developing a Roadmap and Plan
• Q&A
22
Copyright 2014 by Data Blueprint
23. Measuring Business Value
Define success criteria as specific metrics
• Not always intuitive and at first seems difficult
• Must be done in collaboration with your business partners
If something is important to the business it can be observed. If it can
be observed, it is measureable!
• Understanding ‘measurement’; reducing uncertainty, not necessarily
an exact value
• Object of Measurement; often too ambiguously defined
• Methods of Measurement; become familiar with multiple methods and
apply in the right context
23
Copyright 2014 by Data Blueprint
24. Great point of initial
inspiration ...
• Formalizing stuff forces
clarity
• Special shout out to
Chapter 7
– Measuring the value of
information
– ISBN: 0470539399
– http://www.amazon.com/
How-Measure-AnythingIntangibles-Business
24
Copyright 2014 by Data Blueprint
25. Measuring Business Value – An Example
International Chemical Company Engine Testing
• $1billion (+) chemical company
• Develops/manufactures additives
enhancing the performance of oils
and fuels ...
• ... to enhance engine/machine
performance
– Helps fuels burn cleaner
– Engines run smoother
– Machines last longer
• Tens of thousands of
tests annually ($25K to $250K each)
25
Copyright 2014 by Data Blueprint
26. Objects of Measurement & Metrics
• Test Execution: Number of tests per customer
product formulation. Grouped by product types
and product complexity.
• Customer Satisfaction: Amount of time to
develop a certified custom formulated product;
time from initial request to certification
• Researcher Productivity: Tested and certified
formulations per researcher
Note: Baseline measures were taken from historical data and anecdotal
information
26
Copyright 2014 by Data Blueprint
27. 1. Manual transfer of digital data
2. Manual file movement/duplication
3. Manual data manipulation
4. Disparate synonym reconciliation
5. Tribal knowledge requirements
6. Non-sustainable technology
Overview of Existing Process
27
Copyright 2014 by Data Blueprint
28. Solution and Business Value Results
• Solution:
–
–
–
–
Business process improvements
Data Architecture Development
Data Quality Improvements
Integrated System Development
• Results:
– Reduced the number of tests needed to develop products
– Increase the number of tests per researcher
– Reduce the time to market for new product development
• According to our client’s internal business case development,
they expect to realize a $25 million gain each year thanks to
this data integration
28
Copyright 2014 by Data Blueprint
29. Summary – Measuring Business Value
• If it’s important to the business, it’s measureable
• Learning to measure business value requires:
– Understanding fundamentally what it means to ‘measure’
– Being clear about what is going to be the object of
measurement and the specific metrics
– Methods that will ensure the metrics captured are
meaningful and consistent
• The old adage – “if you don’t measure it, it can’t be
managed” is true
Next Step:
• Develop a holistic solution and approach to address the
business needs identified in the data strategy
29
Copyright 2014 by Data Blueprint
30. Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– An Example
• Measurement & Success Criteria
– An Overview
– An Example
• Developing a Solution to Address Needs
– Closing Foundational Gaps
– Solving for Specific Business Needs
• Developing a Roadmap and Plan
• Q&A
30
Copyright 2014 by Data Blueprint
31. The Data Strategy Solution
With an understanding of business needs and measures of
success criteria, align a solution leveraging the following:
• Rethink the SDLC: Application- vs. Data-Centric
• Make it Comprehensive:
– People: Organizational Structure
– Data Management Practices: Foundational & Technical
– Data: Determine What is Important
– Process: Business Process Changes
– Technology: Engineering/Architectural Concepts
• Match your organization’s abilities to deliver
31
Copyright 2014 by Data Blueprint
32. Typical Thinking: Application-Centric
•
In support of strategy, organizations develop specific
goals/objectives
•
The goals/objectives drive the development of specific
systems/applications
•
Development of systems/applications leads to network/
infrastructure requirements
•
Data/information are typically considered after the
systems/applications and network/infrastructure have
been articulated
•
Strategy
Goals/Objectives
Systems/Applications
Problems with this approach:
– Ensures data is formed to the applications and not
around the organizational-wide information
requirements
Network/Infrastructure
– Process are narrowly formed around applications
– Very little data reuse is possible
Data/Information
32
Copyright 2014 by Data Blueprint
33. New Thinking: Data-Centric
•
In support of strategy, the organization develops specific
goals/objectives
•
The goals/objectives drive the development of specific
data/information assets with an eye to organization-wide
usage
•
Development of systems/applications is derived from the
data/network architecture
•
Goals/Objectives
Network/infrastructure components are developed to
support organization-wide use of data
•
Strategy
Advantages of this approach:
– Data/information assets are developed from an
organization-wide perspective
Data/Information
Network/Infrastructure
– Systems support organizational data needs and
compliment organizational process flows
– Maximum data/information reuse
Systems/Applications
33
Copyright 2014 by Data Blueprint
34. People: Who is Involved?
• Open question: Who is responsible for creating and implementing
the company’s Data Strategy?
-
Organizational Leadership is required – a Chief Officer that reports up through the business
lines
-
Data strategy requires governance – Business, IT and Data team representation
• Stakeholders
-
CEO, CFO, COO, CIO, etc..
-
Lines of Business Senior Management and Operational Managers
-
Functional Areas Senior Management and Team Leads
• The Data Team – formal and implicit
-
Architects
-
Modelers
-
Developers
-
Analysts
-
Stewards
- CDO
34
Copyright 2014 by Data Blueprint
35. ce
n te
r/I
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tio
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/P
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1. Dedicated solely to
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2. Unconstrained by an
IT project mindset
3. Reporting to the
business
IT
/In
Top Job
CDO Reporting
Top
Information
Technology
Job
Top
Operations
Job
Chief
Data
Officer
Top Finance
Job
0.000
Copyright 2014 by Data Blueprint
Top
Marketing
Job
Data Governance Organization
0.800
0.600
0.400
0.200
2011
2010
2009
2008
2007
2006
2005
35
36. Data: Determine What is Important
• Think about it in terms of data ‘meta-types’:
– Transactional Data
– Workflow/Event Data
– Master & Reference Data
– Reporting & Analytical Data
– Metadata
• Not all of your data is important!
• Concept of ROT
• Understanding your business and their needs
makes this easier to determine
36
Copyright 2014 by Data Blueprint
37. Data Management Practices
• Foundational Data
Management Practices
create the organizational
infrastructure that enforces the
alignment of company
strategies with data assets
• Technology Data
Management Practices
enable an organization to
leverage the data on the scale
needed to support informationbased strategies
Important Note: Not all DM
Practices needed all the time.
Tailor to meet the needs of the
business.
37
Copyright 2014 by Data Blueprint
38. Foundational Practices
• 3-legged stool
– Strategy
– Architecture
– Governance
• For example:
– Warehouses fail
– Missing governance
– Quality
38
Copyright 2014 by Data Blueprint
39. Health Care Provider
Data Warehouse
The average DW costs $30M
and take 18 months to build!
•
•
•
•
1.8 million members
1.4 million providers
800,000 providers no key
1 User
"I can take a roomful of MBAs and accomplish this analysis faster!"
39
Copyright 2014 by Data Blueprint
40. Foundational Practice: Data Strategy
• Your data strategy must align
to your organizational
business strategy and
operating model
• As the market place
becomes more data-driven,
a data-focused business
strategy is an imperative
• For example, you must have
data strategy before you
have a Big Data strategy
40
Copyright 2014 by Data Blueprint
41. Foundational Practice:
Data Architecture
• Common vocabulary
expressing integrated
requirements ensuring that
data assets are stored, arranged,
managed, and used in systems in support of
organizational strategy [Aiken 2010]
• Most organizations have data assets that are not
supportive of strategies
• Big question:
• How can organizations more effectively use their
information architectures to support strategy
implementation?
41
Copyright 2014 by Data Blueprint
42. Foundational Practice:
Data Governance
• Data governance is the
exercise of authority and
control over the management
of your mission critical data
assets.
• Governance can seem like an added bureaucratic
layer with little value-add. The little ‘g’ approach develop governance where it matters the most.
• Focus on organizational roles and responsibilities as
well as organizational change management
initiatives.
42
Copyright 2014 by Data Blueprint
43. Technical Practices
• Think like an engineer
– Holistic
– Integrated
– Driven by Requirements
• For example:
– Unwinding Mainframes
– Analytical Platforms
43
Copyright 2014 by Data Blueprint
44. Technical Practices:
Data Quality
• Quality is driven by fit for
purpose considerations
• Improved directional accuracy is
the goal
• Focus on your most important
data assets and ensure our
solutions address the root cause
of any quality issues – so that
your data is correct when it is
first created
• Experience has shown that
organizations can never get in
front of their data quality issues if
they only use the ‘find-and-fix’
approach
44
Copyright 2014 by Data Blueprint
45. Technical Practices:
Data Integration
• Data integration requires a
common language and
semantic understanding
• Needs to support multiple
perspectives on the same
data
• Creates the broad, 360
degree view – where insight
comes from
• An area where governance
can enable and sustain
• A challenge in organizational
thinking
45
Copyright 2014 by Data Blueprint
46. Technical Practices:
Data Platforms
• Incorporate engineering/
architectural concepts into
holistic systems thinking
• Decouple functionality. No
one data platform can answer
all questions (commonly
misunderstood & expensive)
• Engineered components can
only be as strong as their
weakest component
46
Copyright 2014 by Data Blueprint
47. Getting Data into the Cloud
Transform
Less
Cleaner
More shareable
... data
47
Copyright 2014 by Data Blueprint
48. Technical Practices:
Business Intelligence
• Highly dependent on quality,
metadata, governance,
integration and platforms
• Exploratory in nature. Small
‘failures’ and on-going
learning are part of the
process
• Often exists in spread-marts
and shadow IT solutions –
difficult to share and have a
common understanding
48
Copyright 2014 by Data Blueprint
49. Process: Business Process Impacts
• The Data Strategy Solution will impact existing business processes
and may create new business processes.
• Business processes are how the data get Created, Read, Updated
and Deleted (CRUD)
• A CRUD matrix shows business
processes and their data activity type
• Leverage business process analysis,
design and development techniques
• Capture baseline measures against
existing business processes to effectively measure improvements
49
Copyright 2014 by Data Blueprint
50. Technology: Making the Right Choices
• For example: Software selection
• When it is discovered that the new software doesn't
match existing organizational practices …
1. Change software
2. Change your business practices
3. Some combination of both
4. Ignore the problem
• Data strategy would have
revealed the problem in
advance of the selection
50
Copyright 2014 by Data Blueprint
51. Match your Abilities to Deliver
Understanding your level of Data Management Practice is critical in developing
achievable solutions
Data management
processes and
infrastructure
Organizational Strategies
Implementation
Guidance
Data Program
Coordination
Goals
Organizational
Data Integration
Combining multiple
assets to produce
extra value
Organizational-entity
subject area data
integration
Integrated
Models
Achieve sharing of data within
a business area
Data
Stewardship
Standard
Data
Application
Models &
Designs
Provide reliable
data access
Direction
Data Support
Operations
Feedback
Leverage data in organizational activities
Data
Development
Business
Data
Data
Asset Use
Business Value
51
Copyright 2014 by Data Blueprint
54. Summary: The Data Strategy Solution
• Thinking differently about the solution
• Its Comprehensive: People, Data Management,
Data, Process & Technology
• Address foundational gaps to sustain solutions
• Match your organization’s abilities to deliver
Next Step:
• Outline an achievable implementation plan
54
Copyright 2014 by Data Blueprint
55. Outline
• Data Strategy Overview
• Determining the Business Needs
– Foundational Business Understanding
– Identify Specific Business Needs
– An Example
• Measurement & Success Criteria
– An Overview
– An Example
• Developing a Solution to Address Needs
– Closing Foundational Gaps
– Solving for Specific Business Needs
• Developing a Roadmap and Plan
• Q&A
55
Copyright 2014 by Data Blueprint
56. Implementation Plan & Roadmap
• Outline a long-term vision and implementation milestones
• Achievable, realistic plans
• Build momentum with specific, short-term win projects
– Approach: Crawl, Walk, Run
• More to come at EDW…
56
Copyright 2014 by Data Blueprint
57. The Approach of Crawl, Walk, Run
• Crawl:
– Identify business opportunity and determine a scope that fosters
early learning yet delivers measureable value
• Walk:
– Develop foundational &
technical data management
practices ensuring they are
repeatable. Enlarge the
scope of projects that
expand capabilities
• Run:
– Continuous improvement and expanded application of maturing
data management practices
57
Copyright 2014 by Data Blueprint
58. The Benefits of Crawl, Walk, Run
• ‘Pilot-like’ projects create a unique opportunity for
organizational learning while providing measureable
value
• Builds support for new approaches to data management
– i.e. supports change management activities
• More achievable approach to managing data as an asset
• Allows for foundational components to be developed
while concurrently executing more tactical solutions
58
Copyright 2014 by Data Blueprint
59. Sessions:
• Implementing a Data-Centric
Strategy & Roadmap – Focus on
What Really Matters
– 3 hour workshop with Peter &
Lewis
• Choosing the Right Data
Warehouse Modeling Strategy
based on your business needs:
Kimball, Inmon, Data Vault
– Lighting Talk with Data Blueprint
Team
• 120+ thought leaders
• 800 attending Senior IT
Managers, Architects, Analysts,
Architects & Business Executives
• 5 full days of in-depth education
and networking opportunities
• … and more!!!
• Register here:
www.edw2014.dataversity.net
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60. Questions?
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61. Upcoming Events
Emerging Trends in Data Jobs
March 13, 2014 @ 2:00 PM ET/11:00 AM PT
Data Quality Engineering
April 11, 2014 @ 2:00 PM ET/11:00 AM PT
Sign up here:
• www.datablueprint.com/webinar-schedule
• or www.dataversity.net
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