This is a slide deck that was assembled as a result of months of Project work at a Global Multinational. Collaboration with some incredibly smart people resulted in content that I wish I had come across prior to having to have assembled this.
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 will provide 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.
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.
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.
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.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
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 will provide 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.
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.
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.
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.
Improving Data Literacy Around Data ArchitectureDATAVERSITY
Data Literacy is an increasing concern, as organizations look to become more data-driven. As the rise of the citizen data scientist and self-service data analytics becomes increasingly common, the need for business users to understand core Data Management fundamentals is more important than ever. At the same time, technical roles need a strong foundation in Data Architecture principles and best practices. Join this webinar to understand the key components of Data Literacy, and practical ways to implement a Data Literacy program in your organization.
How to Build & Sustain a Data Governance Operating Model DATUM LLC
Learn how to execute a data governance strategy through creation of a successful business case and operating model.
Originally presented to an audience of 400+ at the Master Data Management & Data Governance Summit.
Visit www.datumstrategy.com for more!
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.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
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
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, 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.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
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.
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
Overcoming the Challenges of your Master Data Management JourneyJean-Michel Franco
This Presentaion runs you through all the key steps of an MDM initiative. It considers and showcase the key milestones and building blocks that you will have to roll-out to make your MDM
journey
-> Please contact Talend for a dedicated interactive sessions with a storyboard by customer domain
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.
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, customer centricity, 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.
Data Management, Metadata Management, and Data Governance – Working TogetherDATAVERSITY
The data disciplines listed in the title must work together. The key to success requires understanding the boundaries and overlaps between the disciplines. Wouldn’t it be great to be able to present the relationships between the disciplines in a simple all-in diagram? At the end of this webinar, you will be able to do just that.
This new RWDG webinar with Bob Seiner will outline how Data Management, Metadata Management, and Data Governance can be optimized to work together. Bob will share a diagram that has successfully communicated the relationship between these disciplines to leadership resulting in the disciplines working in harmony and delivering success.
Bob will share the following in this webinar:
- Categories of disciplines focused on managing data as an asset
- A definition of Data Management that embraces numerous data disciplines
- The importance of Metadata -Management to all data disciplines
- Why data and metadata require formal governance
- A graphic that effectively exhibits the relationship between the disciplines
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
How to identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
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.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
Master Data Management's Place in the Data Governance Landscape CCG
For many organizations, Master Data Management is a necessity to ensure consistency and accuracy of essential business entities. It further plays alongside data architecture, metadata management, data quality, security & privacy, and program management in the Data Governance ecosystem.
Join CCG's data governance subject matter experts as they overview the fundamentals of Master Data Management at our Atlanta-based Data Analytics Meetup. This event will discuss how to enable components of data governance within your organization and review how to best leverage Microsoft's SQL Server Master Data Services.
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
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
Digital Transformation is a top priority for many organizations, and a successful digital journey requires a strong data foundation. Creating this digital transformation requires a number of core data management capabilities such as MDM, 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.
This presentation reports on data governance best practices. Based on a definition of fundamental terms and the business rationale for data governance, a set of case studies from leading companies is presented. The content of this presentation is a result of the Competence Center Corporate Data Quality (CC CDQ) at the University of St. Gallen, Switzerland.
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.
You Need a Data Catalog. Do You Know Why?Precisely
The data catalog has become a popular discussion topic within data management and data governance circles. A data catalog is a central repository that contains metadata for describing data sets, how they are defined, and where to find them. TDWI research indicates that implementing a data catalog is a top priority among organizations we survey. The data catalog can also play an important part in the governance process. It provides features that help ensure data quality, compliance, and that trusted data is used for analysis. Without an in-depth knowledge of data and associated metadata, organizations cannot truly safeguard and govern their data.
Join this on-demand webinar to learn more about the data catalog and its role in data governance efforts.
Topics include:
· Data management challenges and priorities
· The modern data catalog – what it is and why it is important
· The role of the modern data catalog in your data quality and governance programs
· The kinds of information that should be in your data catalog and why
Data Modeling, Data Governance, & Data QualityDATAVERSITY
Data Governance is often referred to as the people, processes, and policies around data and information, and these aspects are critical to the success of any data governance implementation. But just as critical is the technical infrastructure that supports the diverse data environments that run the business. Data models can be the critical link between business definitions and rules and the technical data systems that support them. Without the valuable metadata these models provide, data governance often lacks the “teeth” to be applied in operational and reporting systems.
Join Donna Burbank and her guest, Nigel Turner, as they discuss how data models & metadata-driven data governance can be applied in your organization in order to achieve improved data quality.
Gartner: Master Data Management FunctionalityGartner
Gartner will further examine key trends shaping the future MDM market during the Gartner MDM Summit 2011, 2-3 February in London. More information at www.europe.gartner.com/mdm
Data Governance — Aligning Technical and Business ApproachesDATAVERSITY
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the “glue” that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
Overcoming the Challenges of your Master Data Management JourneyJean-Michel Franco
This Presentaion runs you through all the key steps of an MDM initiative. It considers and showcase the key milestones and building blocks that you will have to roll-out to make your MDM
journey
-> Please contact Talend for a dedicated interactive sessions with a storyboard by customer domain
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.
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, customer centricity, 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.
Data Management, Metadata Management, and Data Governance – Working TogetherDATAVERSITY
The data disciplines listed in the title must work together. The key to success requires understanding the boundaries and overlaps between the disciplines. Wouldn’t it be great to be able to present the relationships between the disciplines in a simple all-in diagram? At the end of this webinar, you will be able to do just that.
This new RWDG webinar with Bob Seiner will outline how Data Management, Metadata Management, and Data Governance can be optimized to work together. Bob will share a diagram that has successfully communicated the relationship between these disciplines to leadership resulting in the disciplines working in harmony and delivering success.
Bob will share the following in this webinar:
- Categories of disciplines focused on managing data as an asset
- A definition of Data Management that embraces numerous data disciplines
- The importance of Metadata -Management to all data disciplines
- Why data and metadata require formal governance
- A graphic that effectively exhibits the relationship between the disciplines
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
To take a “ready, aim, fire” tactic to implement Data Governance, many organizations assess themselves against industry best practices. The process is not difficult or time-consuming and can directly assure that your activities target your specific needs. Best practices are always a strong place to start.
Join Bob Seiner for this popular RWDG topic, where he will provide the information you need to set your program in the best possible direction. Bob will walk you through the steps of conducting an assessment and share with you a set of typical results from taking this action. You may be surprised at how easy it is to organize the assessment and may hear results that stimulate the actions that you need to take.
In this webinar, Bob will share:
- The value of performing a Data Governance best practice assessment
- A practical list of industry Data Governance best practices
- Criteria to determine if a practice is best practice
- Steps to follow to complete an assessment
- Typical recommendations and actions that result from an assessment
How to identify the correct Master Data subject areas & tooling for your MDM...Christopher Bradley
1. What are the different Master Data Management (MDM) architectures?
2. How can you identify the correct Master Data subject areas & tooling for your MDM initiative?
3. A reference architecture for MDM.
4. Selection criteria for MDM tooling.
chris.bradley@dmadvisors.co.uk
Tutustuminen data-analytiikan ja big datan maailmaanJari Jussila
Tutustuminen data-analytiikan ja big datan maailmaan. Valikoitua sisältöä Edutech Data ja analytiikka liiketoiminnan kehittämisessä koulutuspäivästä. Kouluttajina Pasi Hellsten & Jari Jussila. @EdutechTUT #Data4BizTraining
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
Introduction to Microsoft’s Master Data Services (MDS)James Serra
Master Data Services is bundled with SQL Server 2012 to help resolve many of the Master Data Management issues that companies are faced with when integrating data. In this session, James will show an overview of Master Data Services 2012, including the out of the box Web UI, the highly developed Excel Add-in, and how to get started with loading MDS with your data.
Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring.
Data-Ed Webinar: Data Quality EngineeringDATAVERSITY
Organizations must realize what it means to utilize data quality management in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring.
Takeaways:
Understanding foundational data quality concepts based on the DAMA DMBOK
Utilizing data quality engineering in support of business strategy
Data Quality guiding principles & best practices
Steps for improving data quality at your organization
About Element22 - Unlocking The Power Of DataElement22
Element22 is a boutique data management advisory, design and technology solutions firm for the financial services industry. On a daily basis, we work with financial institutions to transfer them into data-driven organizations and meet regulatory requirements, such as BCBS 239.
Increasing Your Business Data & Analytics MaturityMario Faria
Slides of the webinar presented July 10th. The audio can be accessed at : http://www.dataversity.net/webinar-increasing-business-data-analytics-maturity-2/
Achieving a Single View of Business – Critical Data with Master Data ManagementDATAVERSITY
Organizations today are critically reliant on data. However, as enterprise applications accumulate—often through digital transformation initiatives, new product launches, or mergers and acquisitions—business-critical data becomes increasingly siloed. As a result, organizations struggle to gain a complete view of customers, products, business partners, or other data domains scattered across legacy systems, cloud, databases, and spreadsheets—typically featuring unique ways of defining, modeling, and recording master data. Working with a network of vendors and suppliers, each with their own array of applications and data systems, only complicates the picture further. All of which inhibits an organization’s ability to realize value from their data. Master Data Management (MDM) allows organizations to consolidate data from multiple sources to create a single source of truth that provides a holistic view of enterprise-wide information. Join this webinar to discover how multi-domain MDM can eliminate the guesswork and uncertainty that results from data gaps and inconsistencies, paving the way for new, powerful insights through cross-domain intelligence.
Topics covered will include:
- Following a proven method to define and execute a data harmonization strategy that’s directly aligned with business objectives and outcomes
- Establishing a ‘contextually relevant’ golden record of consistent, valid, and accurate data across domains, applications, and services
- Creating linked relationships between data domains and surfacing up analytics on different data types to provide context and enable more informed decision-making
- Ensuring that your data governance strategy both complements and supports your data harmonization and consolidation approach
- Managing all administrative, stewardship, and governance functions across domains from a single user interface
- Allowing various user personas to utilize data and collaborate effectively with structured operating models that are ‘fit for purpose’
- Ultimately achieving a single view of critical data and related data elements that is easy to navigate
Enterprise Data Management Framework OverviewJohn Bao Vuu
A solid data management foundation to support big data analytics and more importantly a data-driven culture is necessary for today’s organizations.
A mature Data Management Program can reduce operational costs and enable rapid business growth and development. Data Management program must evolve to monetize data assets, deliver breakthrough innovation and help drive business strategies in new markets.
Increasing Your Business Data and Analytics MaturityDATAVERSITY
For a few years now, companies of all sizes have been looking at data as a lever to increase revenues, reduce costs or improve efficiency. However, we believe the power of using data as a strategic asset is still in its early stages. One of the main reasons for that is business leaders still do not understand that the data & analytics maturity should be seen as a long time journey and an evolving enterprise learning. This webinar will present some key points on how data management leaders can succeed in their mission by sharing some practical experiences.
Joe Caserta, President at Caserta Concepts presented at the 3rd Annual Enterprise DATAVERSITY conference. The emphasis of this year's agenda is on the key strategies and architecture necessary to create a successful, modern data analytics organization.
Joe Caserta presented What Data Do You Have and Where is it?
For more information on the services offered by Caserta Concepts, visit out website at http://casertaconcepts.com/.
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2. MDM BI – Vision
Transaction
Systems
Business Process Management
Capture Consume
Master Data Management
Instantiate Provide
Monitor
Business Intelligence
Data
Warehouse
Big Data
Visualization
Goals:
• Enable Speed of Innovation for MDM BI activities across the
Enterprise, the Operational Units, and the Business Users
• Define Governance and Data Management Practices
throughout the Enterprise
• Improve the accuracy of Master Data for Unity and Legacy
Systems
• Build Enterprise Class Metrics and KPIs based on Business
Processes
3. Enterprise
• Data Stewards
• Data Governance
• BI Team
• Technology Team
Operational Unit
• MDM BI COEs
• BRM Teams
• Data Scientists
• Data Analysts
Business Users
• Data Stewards
• Reporting Stewards
Operational Unit
Business UsersEnterprise
Ideation
Transaction
and KPI
Consumption
Self
Service
Requirements
Data ProfilingGovernance
Visualization Testing
Publishing
Architecture
Standards
Methods
Technologies
Training
Solution Design
Data Ingestion
Analytic
Algorithms
Data
Exploration
Application
Development
Master Data
Business
Intelligence
Big Data
Data
Cleansing
MDM BI – Roles and Functions
4. Business Data Governance – Overview
Master Data
Management
DW & BI
Management
Data Quality
Management
Metadata
Management
Data Security
Management
Data
Architecture
Management
Data
Development
Misconception Reality
It's an IT responsibility
Data Governance requires a partnership between Business,
Technology, and Operations
One size fits all
The organization, processes, and technology must be tailored to
fit the culture and leverage existing governance structures and
technology
It can succeed through a grass
roots bottoms up effort
Success requires executive advocacy and sponsorship
It's about having the right tools
Data governance requires the integration of organization,
processes, and technology tools
It can be an add on
responsibility that doesn't need
to be measured or rewarded
Data stewardship may require full time staff commitment. If the
role is not measured or rewarded, the result will be ineffective
governance action
It’s a big bang implementation
Standing up data governance structures is an evolutionary
process that requires effective change management
Data governance is the orchestration of people, process, and
technology to enable the leveraging of data as an enterprise
asset through a well-defined organizational structure,
policies, rules, decision rights and accountabilities for
decision making and management of Master Data.
5. Data Governance – 180 Day Plan
•Create the appropriate review and escalation methods for managing data quality and integrity
•Enable the linkage between business process/data owners who “champion” data and metrics with the data
architects and data stewards who manage the transaction level detail
Governance
&
Stewardship
•Integrate roles across functions (e.g., data cleansing, data architects, data stewards, process/data owners)
•Understand the needs of the consumer of the data and connect appropriately
People/
Organization
•Define end to end, consistent processes across all data types, linking transaction level data with Management
Information
•Define proper controls to manage data quality and integrity on a sustainable basis
Process
•Identify Tools for cleansing, mapping, identifying anomalies, etc.
•Leverage data management tools and infrastructure that have rapid scalability and functionality
•Define consistent architecture that enables “one version of the truth”
Technology
6. MDM BI
Data Cleansing
MDM BI
Product
MDM BI
Customer
MDM BI
Vendor
MDM BI
Operational
MDM BI
Financial
MDM BI
Stat/Mgmt Rptg
EBPM - PTP
EBPM - PTD
EBPM - OTC
EBPM - RTR
EBPM - FTP
As requirements for
MDM and KPIs are
assembled,
PRIORITIZATION and
sequence can be
further refined
Outcomes
MDM BI – Discovery Approach
Enterprise
Data Model
Master Data
Models
Required
KPIs
7. MDM BI – Deployment Approach
Discovery Analyze / Define Design
Deliverable
• Conduct Discovery
Sessions
• Define Solution Scope
• Define Solution Concept
• Define General System
Concept
• Describe Potential
Impact
• Plan Project
• Analyze Guidance
Architecture
• Analyze Data
Architecture
• Create Data Schema
Map
• Assess Data Quality
• Analyze System
Architecture
• Analyze System
Requirements
• Design Guidance
Architecture
• Design Data
Architecture
• Design System
Architecture
Design Application
Specification
• Design Data Migration
• Design Human
Transition Support
Activity
• Discovery Summary
• Solution Scope
• Solution Concept
• System Concept
• Impact Summary
• Project Plan
• Organizational Model
• Guidance Model
• Data Model
• Data Schema Map
• Data Quality
Assessment
• System Interaction
Diagram
• System Requirements
Summary
• Organizational Model
• Guidance Model Data
Model
• System Interaction
Diagram
• Application Specification
Data Migration Plan
• Organization Change
Management Plan
• Training Plan
• Discovery & Analyze initiated via
common stakeholder interviews
• Design & Build executed on
Global Template
• SAP Deployments will review
efforts from previous phases but
largely be testing and refining
exercise
Build Test Deploy Sustain
8. MDM – Implementation Approaches
Consolidation Registry Coexistence Centralized
For Reporting, analysis, and
central reference
Mainly for real-time central
reference
For harmonization across
databases and for central
reference
Acts as system of record to
support transactional activity
Matches and physically stores a
consolidated view of master
data
Matches and links to create a
“skeleton” system of record
Matches and physically stores a
consolidated view of master
data
Matches and physically stores
the up-to-date consolidated
view of master data
Updated after the event and not
guaranteed up-to-date;
authoring remains distributed
Physically stores the Global ID,
links to data in source systems
and transformations
Updated after the event and not
guaranteed up-to-date;
authoring remains distributed
Supports transactional
applications directly – both new
and legacy – typically through
SOA interfaces
No publish and subscribe; not
used for transactions but could
be used for reference
Virtual consolidated view is
assembled dynamically and is
often read-only; authoring
remains distributed
Publishes the consolidated view;
not usually used for transactions
but could be used for reference
Central authoring of master data
Analytical Focus Operational Focus Operational Focus Operational Focus
System of Reference System of Reference System of Reference System of Record
9. Enterprise
Master Data
Model
Legacy
ERP
MDM People
MDM Processes
MDM Tools
Transformation
Certified Master
Data
2
3
4
1. Non-Certified Data from the
Legacy Systems is ingested and
transformed into the Enterprise
Master Data Model built during
the Discovery Phase
2. The Enterprise Data Model is
adjusted as necessary and
cleansed data is pushed back to
the Legacy ERP System
3. Certified Master Data is produced
and the required refinements to
processes and data architecture
are made to enable downstream
consumption
4. All of this is enabled by dedicated
MDM personnel, utilizing MDM
tools and processes
MDM – Pre-Cleanse & Deployment Process
1
Non-Certified
Data
10. BI – Ownership Structure
Sandbox (50%)
[user created content]
Shared (30%)
[user created and shared
content]
Production
(20%)
Gather
Data
Visualize
PublishConsume
Ideate
Business
Users
Require-
ments
Profile
Data
DesignDevelop
Test
IT
Sandbox Environment
• Business users author and use BI content with no
constraints or limitations. This is where data
exploration, discovery, and what-if analyses
happen.
• Tools and technologies: Microsoft Office
• IT involvement is strictly limited to infrastructure
and tools support plus monitoring to identify
usage patterns, commonalities, and opportunities
(using BI on BI) for potential production
hardening.
• Content produced here is used in individual tasks
and low-risk applications.
Shared Environment
• Business users share and collaborate on BI content
with their colleagues.
• Tools and technologies: SharePoint BI, Office 365
• IT steps up monitoring and now watches for red
flags (too much data, too many users, too critical
or risky applications) and opportunities (using BI
on BI) for production hardened BI Content.
• Content produced here is shared within
departments and workgroups. Low-risk, low-
criticality decisions can be made based on this
content.
Production Environment
• Business uses and authors BI content within the
limitations and constraints of the enterprise data
model, standards, policies, rules, guidelines, etc.
• Tools and technologies: EDW, Visual Studio,
SharePoint BI, Office 365
• Owned, run, and managed by IT.
IT Benefits
• Backlog Reduction – only heavily-used,
complex, or critical applications come to IT for
production-hardening.
• Requirements already defined; Project Lifecycle
is greatly reduced; Enhancements during
testing cycle minimized.
• Shadow IT is embraced as a competitive
advantage; however, using the strategic
technology stack defined by IT.
Business Benefits
• Business users are empowered to
create BI content on their own
schedule without any constraints
or limitations – at the speed of
business innovation.
• They modify the model and
visualizations through iteration until
the requirements are identified and
met.
11. Hadoop = Data Lake
• Land all data in Hadoop as-is from any source
• Enables Analytics Sandbox
• Enables MDM Pre-Processing
• Enables EDW Population with Relevant Data
• Enables Application Access via API Layer (including 3rd party
developers)
Actively Archive from EDW to Hadoop
• Little-Used Historic EDW Data resides in Hadoop (lower cost
storage)
• Define an archive strategy for various data types
Enable business analytics
• Identify tools, methods, and security requirements for
interaction with the distributed file system
• Introduce exploratory analytics without jeopardizing SLAs
• Introduce new machine learning, or data mining techniques
on years worth of data
Enable BU Innovation
• BU Teams continue to innovate with their business users
within the Enterprise Framework – ingestions driven by BU OR
Enterprise requirements
• Data Scientists and Analysts can access all Data for Analytics
• BU IT & Business Teams can access all Data for Visualizations
with proper security
• Enterprise Data Model, HDFS Standards, and Access Methods
extensible to manage localizations at the BU level and below
BI – Data Flows
Data Sources/Transports
Transaction Data
Customer Data
External Data
Industry Data
Sensor Data
DB
Files
REST
JMS
HTTP
SOAP
Hadoop
Compute +
storage
… … …
… … … …
… … … …
… … …
Compute +
storage
supporting technologies& packages
EDW
BI Tools & Applications
Query & Visualization Tools
JDBC/ODBC Compliant
Tools & Applications
Analytic & Reporting Tools
R
Mahout
Excel
Excel
PowerPoint
Power View
MDM
API Layer
BU1 BU2 BUn
BU1 BU2 BUn
BU1 BU2 BUn
12. Establish, Maintain, and
Periodically Review and
Recommend Changes to Data
Governance Policies, Standards,
Guidelines, and Procedures
The Team responsible to develop the strategy,
govern the tools selected to acquire and transform
relevant data into knowledge to drive business
decisions and actions to achieve desired results. In
addition, the resulting information has to be
tailored to – and distributed to – the appropriate
levels of management and operations in a timely
manner to be most effective. In some cases BI
Execution of Reporting and Analytics is performed
as well.
Provide Quality Assurance –
Oversight, Monitor, Report Results
to Data Governance Council
VP MDM & BI
Business
Governance
Leader
Data Stewards
by Domain
Data Stewards
by Business Unit
Data
Governance
Leader
Data Quality
Data
Architecture
Data
Conversions
Big Data
Architect
BI Governance
Leader
BI Leads
BI Visualization
Developers -
Enterprise
BI ETL
Developers -
Enterprise
BI Developers –
Business Units
Technology &
Tools Leader
Technology
SMEs
DBAs
System SMEs
• Develop and Deliver Data Governance
Program Educational, Awareness &
Mentoring Materials
• Assist in Defining Data Quality Metrics
for Periodic Release
• Support Data Quality Issue Analysis and
Remediation for “Strategic” Data
• Oversee Enterprise Data Governance
Program Development / Architect
Solution & Framework
• Administer the Program including
facilitate the Data Governance Council
meetings
• Provide the Agenda for the Data
Governance Council Meetings to the
Approved by Council Owner Pre-
Meeting
• Facilitate Data Governance Organization,
Tactical & Operational Stewards, the
Data Governance Council Involvement
• Conduct Audits to Ensure that Policies,
Procedures and Metrics are in Place for
Maintaining/Improving the Program
Functionally
Aligned Roles
Organizationally
Aligned Roles
Sample Organization
