Acting on Analytics - How to Build a Data-Driven Enterprise - Brighttalk webi...Mario Faria
Big Data and Analytics have become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, there is one component that can halt any initiative: YOUR COMPANY's ANALYTICS MATURITY.
How prepared is your company to implement and use the available data, the high end modeling techniques and the data as well as analytics expertise?
From what I have learned and experienced, companies are still not adequately prepared, hurting their ability to compete in the market.
This presentation will help executives and data professionals to understand the steps needed to create an analytics organization, and provide some real life examples on companies who succeeded and some who failed miserably.
3 Steps to Becoming a Successful Chief Data OfficerMario Faria
Presentation delivered at the Enteprise Data Leadership Summit, in Chicago March-2014
Mario Faria, Head of Chief Data Officer, Inc., a consulting and advisory services company, based in Seattle, WA
Using Lean Principles to Manage the Data Value ChainMario Faria
Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.
Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.
This session delivered for the Data Quality Pro Summit explores how it can be done.
The Rise of People Management AnalyticsMario Faria
Data is now as integral to our 21st century economy as oil has been for many decades. With the power of data and analytics, several organizations are rethinking their business strategy completely.
However, when we look at data and analytics from an HR or people management perspective, there are some untapped opportunities to make data-driven decisions. What are some of these opportunities? Does a culture change need to happen to positively impact your company’s bottom-line?
This is the material I used at my session at the Great Place to Work Institute in Canada, on April 2015.
I discussed these questions and share case studies on how some organizations are now using their second most important asset (data) to manage their most important asset (people).
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/
The Chief Data Officer - quotes from data & analytics thought leadersMario Faria
Data & Analytics have become so important on how business are differentiating themselves in the marketplace. With the help from the most well recognized data leaders of our time, I have put together their thoughts in this material. By sharing our thinking, we want companies to understand what it takes to become a data-driven organization.
Acting on Analytics - How to Build a Data-Driven Enterprise - Brighttalk webi...Mario Faria
Big Data and Analytics have become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, there is one component that can halt any initiative: YOUR COMPANY's ANALYTICS MATURITY.
How prepared is your company to implement and use the available data, the high end modeling techniques and the data as well as analytics expertise?
From what I have learned and experienced, companies are still not adequately prepared, hurting their ability to compete in the market.
This presentation will help executives and data professionals to understand the steps needed to create an analytics organization, and provide some real life examples on companies who succeeded and some who failed miserably.
3 Steps to Becoming a Successful Chief Data OfficerMario Faria
Presentation delivered at the Enteprise Data Leadership Summit, in Chicago March-2014
Mario Faria, Head of Chief Data Officer, Inc., a consulting and advisory services company, based in Seattle, WA
Using Lean Principles to Manage the Data Value ChainMario Faria
Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.
Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.
This session delivered for the Data Quality Pro Summit explores how it can be done.
The Rise of People Management AnalyticsMario Faria
Data is now as integral to our 21st century economy as oil has been for many decades. With the power of data and analytics, several organizations are rethinking their business strategy completely.
However, when we look at data and analytics from an HR or people management perspective, there are some untapped opportunities to make data-driven decisions. What are some of these opportunities? Does a culture change need to happen to positively impact your company’s bottom-line?
This is the material I used at my session at the Great Place to Work Institute in Canada, on April 2015.
I discussed these questions and share case studies on how some organizations are now using their second most important asset (data) to manage their most important asset (people).
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/
The Chief Data Officer - quotes from data & analytics thought leadersMario Faria
Data & Analytics have become so important on how business are differentiating themselves in the marketplace. With the help from the most well recognized data leaders of our time, I have put together their thoughts in this material. By sharing our thinking, we want companies to understand what it takes to become a data-driven organization.
In many organizations and functional areas, data has pulled even with money in terms of what makes the proverbial world go round. As businesses struggle to cope with the 21st century’s newfound data flood, it is more important than ever before to prioritize data as an asset that directly supports business imperatives. However, while organizations across most industries make some attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. Data Quality), the results of these efforts frequently fall far below expectations. At the root of many of these failures is poor organizational Data Management—which fortunately is a remediable problem.
This webinar will cover three lessons, each illustrated with examples, that will help you establish realistic goals and benchmarks for Data Management processes and communicate their value to both internal and external decision-makers:
How organizational thinking must change to include value-added Data Management practices
The importance of walking before you run with data-focused initiatives
Prioritizing specification and Data Governance over “silver bullet” analytical tools
Discuss foundational data-centric concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Go Social or Die: Why Digital Competence Can't Be Ignoredjonnie jensen
Too many businesses are not embracing digital and social technologies. Stuck in the comfort of their existing processes and frightened by tabloid headlines they fear losing control. Ultimately though new technologies result in higher productivity and increased revenues. The choice about achieving digital competence in your business is no longer choice. Quite simply it is go social…or die.
Startup and Growth companies that have unique and compelling product ideas still need to find a strategic pathway towards building that vision into a final product. Designing and building features is just part of the puzzle and fast iterations are only helpful if you are gaining real and useful learning from those releases. Data strategy ensures that each product feature released is backed by data to measure its impact and effectiveness.
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Keys to Creating an Analytics-Driven CultureDATAVERSITY
Changing company culture takes time, energy and focus, as well as consistent reinforcement long after the breakrooms’ company culture posters start to fade. Creating an analytics-driven culture may be even harder to grow and sustain. Yet the rewards are vast for companies whose culture embodies an analytics-first mindset – and for those who use the derived insights to improve operational efficiency and decision-making, generate new revenue and prevent risk and fraud.
This webinar will offer advice and real-world examples on how to:
Develop and utilize an analytics-focused vision statement
Engage senior leaders to support analytics as a business problem-solver
Communication best practices to engage participants in the culture change
Use tried-and-tested best practices and approaches to build an analytics-driven culture
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.
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
Data governance 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 the business objectives and imperatives that demand governance. This webinar also provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these governance aspects is necessary to eliminate the ambiguity that often surrounds effective data governance and stewardship programs. The goal of governance is to manage the data that supports 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
This practical presentation will cover the most important and impactful artifacts and deliverables needed to implement and sustain governance. Rather than speak hypothetically about what output is needed from governance, it covers and reviews artifact templates to help you re-create them in your organization.
Topics covered:
- Which artifacts are most important to get started
- Important artifacts for more mature programs
- How to ensure the artifacts are used and implemented, not just written
- How to integrate governance artifacts into operational processes
- Who should be involved in creating the deliverables
ADV Slides: Databases vs Hadoop vs Cloud StorageDATAVERSITY
Relational databases are old technology, right? Thirty years is a long time for a technology foundation to be as active as relational databases, but, like NFL coaches, we must “tolerate them until we can replace them.” Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage options like a kid in a candy store? We’ll discuss Hadoop’s continued potential relevance and the cloud storage option that seems vital. Use what when? This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.
Drop the herd mentality. In reality, there is no “one size fits all” right now. We need to make our platform decisions against this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2019 for success.
APM Programme Management SIG Conference
Equipping Programme Managers for Global Success -Programme Management: how digital competence creates market leaders, Jonnie Jensen, 10 March 2016
Introduction to Data Governance
Seminar hosted by Embarcadero technologies, where Christopher Bradley presented a session on Data Governance.
Drivers for Data Governance & Benefits
Data Governance Framework
Organization & Structures
Roles & responsibilities
Policies & Processes
Programme & Implementation
Reporting & Assurance
First San Francisco Partner's Managing Director, Kelle O'Neal spoke to group of 150+ people at Oracle Open World, October, 2009 about Data Governance and its imperative use of technology to support data quality in large organizations.
Most of the attention around Analytics goes to the results of the Analytics activity - a better customer profile, a new target market, more efficient product design. What about the process and infrastructure that is needed to get the data to the point in which it is useful to the Analytics community? This presentation addresses the less glamorous, but critically important side of Analytics: the people, process and technology infrastructure that enable an analytics-driven organization.
The presentation will cover these questions:
• How do you align your information assets to your Analytics goals? What data do you need and where do you find it?
• What are the organizational constructs that need to be considered to integrate Data Governance and Analytics?
• What organizational change can be anticipated and how should it be addressed?
• How do you design your data management and data governance programs to support Analytics? How is this different than an operational use case?
This slide deck is drawn from a tutorial presented jointly with Samra Sulaiman of ConsultData at Enterprise Dataversity 2015.
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)
Data Mining: The Top 3 Things You Need to Know to Achieve Business Improvemen...Dr. Cedric Alford
While companies have been using various CRM and automation technologies for many years to capture and retain traditional business data, these existing technologies were not built to handle the massive explosion in data that is occurring today. The shift started nearly 10 years ago with expanding usage of the internet and the introduction of social media. But the pace has accelerated in the past five years following the introduction of smart phones and digital devices such as tablets and GPS devices. The continued rise in these technologies is creating a constant increase in complex data on a daily basis.
The result? Many companies don't know how to get value and insights from the massive amounts of data they have today. Worse yet, many more are uncertain how to leverage this data glut for business advantage tomorrow. In this white paper, we will explore three important things to know about big data and how companies can achieve major business benefits and improvements through effective data mining of their own big data.
Dr. Cedric Alford provides a roadmap for organizations seeking to understand how to make Big Data actionable.
This presentation provides you with an understanding of reference and master data management (MDM) goals, including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivering data to various business processes, and increasing the quality of information used in organizational analytical functions (such as BI). Attendees will learn how to incorporate data quality engineering into the planning of reference and MDM. Finally, we will discuss why MDM is so critical to the organization’s overall data strategy.
Takeaways:
•What is reference and MDM?
•Why are reference and MDM important?
•How to use Reference and MDM Frameworks
•Guiding principles & best practices for MDM
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)
Data-Ed Online: Data Management Maturity ModelDATAVERSITY
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization's data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.
Takeaways:
Our profession is advancing its knowledge and has a wide spread basis for partnerships
New industry assessment standard is based on successful CMM/CMMI foundation
Clear need for data strategy
A clear and unambiguous call for participation
About the Speakers
Was Big Data worth it? We were promised a data revolution when Big Data and Hadoop exploded onto the scene – but those technologies brought with them ungoverned, underexploited, complex environments that didn’t solve the analytical problems they were supposed to. All is not lost, however. This webcast explores three important things we’ve learned from Big Data that can be applied to every kind of data environment: modern approaches to data that exploit the flexibility and power of Big Data without losing the governance and management our businesses need.
How to Create and Manage a Successful Analytics OrganizationDATAVERSITY
For the last few years, analytics, data science and data management have achieved tremendous exposure on all the media channels. Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, it is really interesting that just a selected group of business has created successful data teams and has mastered the skills to manage it. What we have seen is that most companies still do not know how to create, implement and manage a data and analytics organization. Above all, if data has become an strategic asset and is being considered the new oil for the 21st century economy, what your strategy to handle it ? This webinar will help to bring some concepts and ideas to enlighten your path to create and manage an analytics organization, providing some real life examples on companies which did it.
In many organizations and functional areas, data has pulled even with money in terms of what makes the proverbial world go round. As businesses struggle to cope with the 21st century’s newfound data flood, it is more important than ever before to prioritize data as an asset that directly supports business imperatives. However, while organizations across most industries make some attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. Data Quality), the results of these efforts frequently fall far below expectations. At the root of many of these failures is poor organizational Data Management—which fortunately is a remediable problem.
This webinar will cover three lessons, each illustrated with examples, that will help you establish realistic goals and benchmarks for Data Management processes and communicate their value to both internal and external decision-makers:
How organizational thinking must change to include value-added Data Management practices
The importance of walking before you run with data-focused initiatives
Prioritizing specification and Data Governance over “silver bullet” analytical tools
Discuss foundational data-centric concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Go Social or Die: Why Digital Competence Can't Be Ignoredjonnie jensen
Too many businesses are not embracing digital and social technologies. Stuck in the comfort of their existing processes and frightened by tabloid headlines they fear losing control. Ultimately though new technologies result in higher productivity and increased revenues. The choice about achieving digital competence in your business is no longer choice. Quite simply it is go social…or die.
Startup and Growth companies that have unique and compelling product ideas still need to find a strategic pathway towards building that vision into a final product. Designing and building features is just part of the puzzle and fast iterations are only helpful if you are gaining real and useful learning from those releases. Data strategy ensures that each product feature released is backed by data to measure its impact and effectiveness.
Big Data and Marketing: Data Activation and ManagementConor Duke
Data Management and Activation
Crevan O’Malley – Evangelist, Oracle Marketing Cloud
Modern Marketers rely on data-driven marketing solutions to deliver more personalised customer experiences across every channel—helping attract and retain the ideal customers who become brand advocates. Discover how to aggregate, enrich, and analyze all your customer data on a single data management platform.
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Why Marketers need to know about Data
Tara Grehan - Managing Director at Datalytics
Despite starting out as a qualitative researcher, roles and projects frequently brought me back to data. And so I decided to tackle it and have developed some interesting insights into data management along the way.
Having worked in Marketing both agency and client side for fifteen years now in a variety of roles from Market Research and Customer Insights to Change Management, being comfortable with data has made all the difference and this evening I’ll tell you why.
Using Big Data to Grow on a Budget
Michael Waldron - Marketing and Sales Manager at AYLIEN
AYLIEN is an Artificial Intelligence content analysis startup and Mike will be speaking on their growth journey over the past 6 months. With a focus on how they have delivered growth by optimising their budget, focusing on Data Points that matter and what to points to obsess on through the marketing funnel.
Keys to Creating an Analytics-Driven CultureDATAVERSITY
Changing company culture takes time, energy and focus, as well as consistent reinforcement long after the breakrooms’ company culture posters start to fade. Creating an analytics-driven culture may be even harder to grow and sustain. Yet the rewards are vast for companies whose culture embodies an analytics-first mindset – and for those who use the derived insights to improve operational efficiency and decision-making, generate new revenue and prevent risk and fraud.
This webinar will offer advice and real-world examples on how to:
Develop and utilize an analytics-focused vision statement
Engage senior leaders to support analytics as a business problem-solver
Communication best practices to engage participants in the culture change
Use tried-and-tested best practices and approaches to build an analytics-driven culture
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.
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
Data governance 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 the business objectives and imperatives that demand governance. This webinar also provides you with an understanding of what data governance functions are required and how they fit with other data management disciplines. Understanding these governance aspects is necessary to eliminate the ambiguity that often surrounds effective data governance and stewardship programs. The goal of governance is to manage the data that supports 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
This practical presentation will cover the most important and impactful artifacts and deliverables needed to implement and sustain governance. Rather than speak hypothetically about what output is needed from governance, it covers and reviews artifact templates to help you re-create them in your organization.
Topics covered:
- Which artifacts are most important to get started
- Important artifacts for more mature programs
- How to ensure the artifacts are used and implemented, not just written
- How to integrate governance artifacts into operational processes
- Who should be involved in creating the deliverables
ADV Slides: Databases vs Hadoop vs Cloud StorageDATAVERSITY
Relational databases are old technology, right? Thirty years is a long time for a technology foundation to be as active as relational databases, but, like NFL coaches, we must “tolerate them until we can replace them.” Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage options like a kid in a candy store? We’ll discuss Hadoop’s continued potential relevance and the cloud storage option that seems vital. Use what when? This is a critical decision that can dictate two to five times additional work effort if it’s a bad fit.
Drop the herd mentality. In reality, there is no “one size fits all” right now. We need to make our platform decisions against this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2019 for success.
APM Programme Management SIG Conference
Equipping Programme Managers for Global Success -Programme Management: how digital competence creates market leaders, Jonnie Jensen, 10 March 2016
Introduction to Data Governance
Seminar hosted by Embarcadero technologies, where Christopher Bradley presented a session on Data Governance.
Drivers for Data Governance & Benefits
Data Governance Framework
Organization & Structures
Roles & responsibilities
Policies & Processes
Programme & Implementation
Reporting & Assurance
First San Francisco Partner's Managing Director, Kelle O'Neal spoke to group of 150+ people at Oracle Open World, October, 2009 about Data Governance and its imperative use of technology to support data quality in large organizations.
Most of the attention around Analytics goes to the results of the Analytics activity - a better customer profile, a new target market, more efficient product design. What about the process and infrastructure that is needed to get the data to the point in which it is useful to the Analytics community? This presentation addresses the less glamorous, but critically important side of Analytics: the people, process and technology infrastructure that enable an analytics-driven organization.
The presentation will cover these questions:
• How do you align your information assets to your Analytics goals? What data do you need and where do you find it?
• What are the organizational constructs that need to be considered to integrate Data Governance and Analytics?
• What organizational change can be anticipated and how should it be addressed?
• How do you design your data management and data governance programs to support Analytics? How is this different than an operational use case?
This slide deck is drawn from a tutorial presented jointly with Samra Sulaiman of ConsultData at Enterprise Dataversity 2015.
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)
Data Mining: The Top 3 Things You Need to Know to Achieve Business Improvemen...Dr. Cedric Alford
While companies have been using various CRM and automation technologies for many years to capture and retain traditional business data, these existing technologies were not built to handle the massive explosion in data that is occurring today. The shift started nearly 10 years ago with expanding usage of the internet and the introduction of social media. But the pace has accelerated in the past five years following the introduction of smart phones and digital devices such as tablets and GPS devices. The continued rise in these technologies is creating a constant increase in complex data on a daily basis.
The result? Many companies don't know how to get value and insights from the massive amounts of data they have today. Worse yet, many more are uncertain how to leverage this data glut for business advantage tomorrow. In this white paper, we will explore three important things to know about big data and how companies can achieve major business benefits and improvements through effective data mining of their own big data.
Dr. Cedric Alford provides a roadmap for organizations seeking to understand how to make Big Data actionable.
This presentation provides you with an understanding of reference and master data management (MDM) goals, including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivering data to various business processes, and increasing the quality of information used in organizational analytical functions (such as BI). Attendees will learn how to incorporate data quality engineering into the planning of reference and MDM. Finally, we will discuss why MDM is so critical to the organization’s overall data strategy.
Takeaways:
•What is reference and MDM?
•Why are reference and MDM important?
•How to use Reference and MDM Frameworks
•Guiding principles & best practices for MDM
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)
Data-Ed Online: Data Management Maturity ModelDATAVERSITY
The Data Management Maturity (DMM) model is a framework for the evaluation and assessment of an organization's data management capabilities. The model allows an organization to evaluate its current state data management capabilities, discover gaps to remediate, and strengths to leverage. The assessment method reveals priorities, business needs, and a clear, rapid path for process improvements. This webinar will describe the DMM, its evolution, and illustrate its use as a roadmap guiding organizational data management improvements.
Takeaways:
Our profession is advancing its knowledge and has a wide spread basis for partnerships
New industry assessment standard is based on successful CMM/CMMI foundation
Clear need for data strategy
A clear and unambiguous call for participation
About the Speakers
Was Big Data worth it? We were promised a data revolution when Big Data and Hadoop exploded onto the scene – but those technologies brought with them ungoverned, underexploited, complex environments that didn’t solve the analytical problems they were supposed to. All is not lost, however. This webcast explores three important things we’ve learned from Big Data that can be applied to every kind of data environment: modern approaches to data that exploit the flexibility and power of Big Data without losing the governance and management our businesses need.
How to Create and Manage a Successful Analytics OrganizationDATAVERSITY
For the last few years, analytics, data science and data management have achieved tremendous exposure on all the media channels. Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, it is really interesting that just a selected group of business has created successful data teams and has mastered the skills to manage it. What we have seen is that most companies still do not know how to create, implement and manage a data and analytics organization. Above all, if data has become an strategic asset and is being considered the new oil for the 21st century economy, what your strategy to handle it ? This webinar will help to bring some concepts and ideas to enlighten your path to create and manage an analytics organization, providing some real life examples on companies which did it.
The Chief Data Officer Golden Rules to Data Quality and Data Governance SuccessMario Faria
At the dawn of 2015, there are around 400 Chief Data Officers working in the world. And that number will double by the end of the year. Everywhere in the world corporations have realized that data can become a lever for competitive advantage.
However, how can CDOs succeed in creating and managing Data Quality and Data Governance initiatives? For my previous personal experiences, I can say it is not an easy task.
This material was delivered in an IAIDQ webinar presented in January 8th 2015. It shows the golden rules a Chief Data or Analytics Officer can apply in order to really make data a pristine asset for the business.
Chief Data & Analytics Officer - who are these new kids on the C-Suite block ?Mario Faria
In the last 12 months, 70% of all the Chief Data Officers in USA were hired. CDOs are the new breed of professionals coming to the C-Suite. They are responsible for handling data as a key strategic asset. In this material, you will be able to understand how they work and what is required to be one successful Chief Data & Analytics Officer
ECMSHOW 2013 - Construindo uma Organização Gerida por DadosMario Faria
Apresentação realizada em São Paulo no dia 08-Outubro-2013 como keynote speaker no evento ECMSHOW 2013, promovido pela Guia Business Media e Revista Information Management
Does your organization need a Chief Data Officer (CDO) ?Mario Faria
A question that will have one answer : it depends ! It depends on your company maturity level and how upper management will support it. This is material I presented at meeting organized by PointB, an strategic consulting company for the data leaders of the Seattle area in Aug-2013
DAS Slides: Data Governance and Data Architecture – Alignment and SynergiesDATAVERSITY
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 and Data Governance for business and IT success.
Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
The Missing Link in Enterprise Data Governance - Automated Metadata ManagementDATAVERSITY
So many companies and organizations are in the same boat. They’re drowning in their data — so much data, from so many different sources. They understand that data governance is hugely important for them to be able to know their data inside and out and comply with regulations. What many companies have not yet come to terms with when implementing their data governance strategy and supporting tools, is the criticality of metadata in the process. As the ‘data about data,’ metadata provides the value and purpose of the data content, thereby becoming an extremely effective tool for quickly locating information – a must for BI groups dealing with analytics and business user reporting.
Octopai's CEO, Amnon Drori will discuss this critical missing link in enterprise data governance and the impact of automating metadata management for data discovery and data lineage for BI. He'll demonstrate how BI groups use Octopai to not only locate their data instantly, but to quickly and accurately visualize and understand the entire data journey to enable the business to move forward.
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 from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
Data Lake Architecture – Modern Strategies & ApproachesDATAVERSITY
Data Lake or Data Swamp? By now, we’ve likely all heard the comparison. Data Lake architectures have the opportunity to provide the ability to integrate vast amounts of disparate data across the organization for strategic business analytic value. But without a proper architecture and metadata management strategy in place, a Data Lake can quickly devolve into a swamp of information that is difficult to understand. This webinar will offer practical strategies to architect and manage your Data Lake in a way that optimizes its success.
DAS Slides: Self-Service Reporting and Data Prep – Benefits & RisksDATAVERSITY
As more organizations see the value of becoming data-driven, an increasing number of business stakeholders want to become more actively involved in the reporting and preparation of critical business data. Tools and technologies have evolved to support this desire, and the ability to manage and analyze vast amounts of disparate data has become more accessible than ever before. With this increased visibility and usage of data, the need for data quality, metadata context, lineage and audit, and other core fundamental best practices is greater than ever.
How can an effective architecture & governance model be created that supports both business agility, as well as long-term sustainability and risk reduction? Where do these responsibilities lie between business and IT stakeholders? Join our panel of experts as they discuss the latest best practices, architectures, and tools that support self-service reporting and data prep to maximize benefits while at the same time reducing risk.
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.
Data Architecture Best Practices for Today’s Rapidly Changing Data LandscapeDATAVERSITY
With the rise of the data-driven organization, the pace of innovation in data-centric technologies has been tremendous. New tools and techniques are emerging at an exponential rate, and it is difficult to keep track of the array of technological choices available to today’s data management professional.
At the same time, core fundamentals such as data quality and metadata management remain critical in order for organizations to obtain true business value from their data. This webinar will help demystify the options available: from data lake to data warehouse, to graph database, to NoSQL, and more, and how to integrate these new technologies with core architectural fundamentals that will help your organization benefit from the quick wins that are possible from these exciting technologies, while at the same time build a longer-term sustainable architecture that will support the inevitable change that will continue in the industry.
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.
Data Architecture Strategies Webinar: Emerging Trends in Data Architecture – ...DATAVERSITY
A robust data architecture is at the core what’s driving today’s innovative, data-driven organizations. From AI to machine learning to Big Data – a strong data architecture is needed in order to be successful, and core fundamentals such as data quality, metadata management, and efficient data storage are more critical than ever.
With the vast array of new technologies available to support these trends, how do you make sense of it all? Our panel of experts will offer their perspectives on how the latest trends in data architecture can support your organization’s data-driven goals.
Organizations across most industries make some attempt to utilize Data Management and Data Strategies. While most organizations have both concepts implemented, they must fully understand the difference to fully achieve their goals.
This webinar will cover three lessons, each illustrated with examples, that will help you distinguish the difference between Data Strategy and Data Management processes and communicate their value to both internal and external decision-makers:
Understanding the difference between Data Strategy and Data Management
Prioritizing organizational Data Management needs vs. Data Strategy needs
Discuss foundational Data Management and Data Strategy concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Similar to Como criar e gerenciar com sucesso uma organização de dados (20)
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.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
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We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
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GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
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Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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GridMate - End to end testing is a critical piece to ensure quality and avoid...
Como criar e gerenciar com sucesso uma organização de dados
1. Mario Faria
1
How to Create and Manage a
Successful Data Organization
Mario Faria
fariamario@hotmail.com
+1 - (425) 628-3517
@mariofaria
2. Mario Faria
2
Who am I ?
• MIT recognition as one of the 1st Chief Data Officers and Lead Data
Scientists in the world (just Google “Mario Faria Chief Data Officer”)
• 20+ years working with Information Technology, Management
Consulting, Financial Services, Retail, CPG and Private Equity
• Proven expertise in Data Management, Data Science, Analytics and
Supply Chain Management
• Speaker at several conferences on the subject in USA, Europe and
Latin America
• Contributor to magazines and publications
• Big Data Advisor at the Bill and Melinda Gates Foundation
• Member of the MIT Data Science Initiative
3. Mario Faria
3
Objectives of this webinar
• Provide insights on how you should successfully create a
Data organization
• With that in place, you will be able to work effectively with
Big Data projects
6. Mario Faria
6
The 3 things:
• Situation : where the market is at this point
• Complication : current issues with data
management and Big Data
• Solution : what I recommend you to do and how
to do it
10. Mario Faria
10
The 4 driving factors that are
changing the technology industry as
we know it
• Social
• Mobile
• Cloud
• Information
11. Mario Faria
11
This brave new world we are living in
• How does success look like in a
world where consumers are now
marketers ?
• Where a trillion data points are
available, alive and transforming
decisions (preference /
purchase) and relationships as
we speak ?
• How to understand, connect and
consistently engage with
consumers and customers
creating loyalty and
recommendations ?
13. Mario Faria
13
“The balance of power in the 21st
century is influenced by the ability
to leverage information assets” –
Gwen Thomas, CEO of The Data
Governance Institute
14. Mario Faria
14
Data is about
• People
• Technology
• Processes
• Modeling
• Analytics
• Communication
• Decisions
• Actions
A data-driven culture is a disruptive factor for entire industries
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What is Analytics ?
“The extensive use of data, statistical
and quantitative analysis, explanatory
and predictive models, and fact-based
management to drive decisions and
actions” – Thomas Davenport
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Analytics is not just about :
• Large volumes
• Greater scope of information
• Real time access to information
• New kind of data and analytics
• Data influx from new technologies
• Non-traditional forms of media
• Variety of sources
It all of the above, plus a transformation in processes and
culture, and it is a disruptive factor for entire industries
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Predictive Analytics
• Prediction is powered by the world's most potent,
booming unnatural resource: data
• Predictive analytics is the science that unleashes the
power of data
Dr.Eric Siegel
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The 3 ingredients to make
Advanced Analytics work
• Choosing the right data and managing multiple data
sources
• Having the capability to build advanced models that turn
the data into insights
• Management must undertake a transformational-change
program so that the insights translate into effective action
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Some problems, at this point, in
most organizations
• Data is fragmented and scattered
• Silos of information hanging around
• Like the truth, data has many versions
• The Data Lifecycle is a complex process
• Data projects being managed by IT
• A formal process to manage data is a
requirement in order to do Analytics
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Confusion between Big Data and
Hadoop
• Hadoop is being wrongly treated as a synonym of
Big Data
• Hadoop is one of the technologies to be used at
Big Data projects
• Hadoop is a great technology for storing
unstructured data in an expensive and scalable
manner, in a high granularity
• What Linux did to Operating Systems, Hadoop is
bringing to Information Management
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And, unfortunately, technology alone will
not change the previous results
To succeed in Data & Analytics, an organization will be
required to change some of its current internal processes
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The catch : just a few companies (users
and consulting) understood the nits and
grits about Data Analytics : it requires you
to moving from a simple data management
vision (tactical) to an information
management vision (strategic)
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What is Data Quality ?
• Quality is a customer perception
• A few dimensions: freshness, coverage,
completeness, accuracy
• It is a never ending job
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More and more, Data Leaders are being hired
to think strategically think about all the steps
from getting raw data and making it useful to
business users
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Foundations of the Data team
responsibilities
• Data Strategy
• Data Analytics
• Data Insights
• Data Architecture
• Data Governance
• Data Quality
• Data Acquisitions
• Data Operations
• Data Policies
• Data Security
• Data Protection
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Chief Data Officer (CDO) /
Chief Analytics Officer (CAO) /
Lead Data Scientist
• A new profession that is becoming very common in
corporations
• He/she is a corporate officer who is the business
leader for enterprise-wide data processing and data
mining.
• The CDO typically reports to the CEO or the COO
and is a member of the executive management team
of a company or business unit.
• CDOs leverage their organization's data assets to
support the business strategy. He/she manages
enterprise-wide data administration and is the
champion of enterprise information management
• CIOs are very concerned with this new role, because
of the threat to their current power
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The role of a Chief Data Officer or
Lead Data Scientist
A data scientist is the one
who looks for insights
The insight is operationalized
in BI/DW products, by data architects
The insight is shared
with the enterprise
The CDO or Lead Data Scientist is the
executive responsible and accountable for
the data life cycle inside the organization,
managing the people involved in the data
activities, such as acquisitions, analytics,
processes, governance, quality, technology
and budget
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Why should not IT be managing
this transition ?
Because data projects are business
projects, not IT projects and the CDO/Data
teams are the bridge between IT and
Business Units
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Why do you need a Chief Data Officer ?
• Data is about business, it's not about
IT
• Data is an economic asset, so you
need a senior person to handle the
data initiatives.
• As an economic asset, data needs:
control, show value and monetization
• There is now way you can do
Advanced Analytics unless you have
some data management practices in
place.
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“Organizations are about to be
swamped with massive data
tsunamis. The Chief Data Officer
is responsible for engineering,
architecting, and delivering
organizational data success” –
Peter Aiken, PhD
67. Data
Science
The
process
of
taking
raw
data,
producing
informa6on
from
data,
and
using
this
informa6on
to
guide
ac6ons
that
will
bring
financial
benefits
to
business
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• A good CDO can implement a data organization
with success
• A great CDO has the ability to turn raw data into
large revenue streams for the business
• Components such as technology and
methodologies are important, but they are just
enablers
• The CDO focus is delivering enterprise value to the
business (not writing code or SQL scripts)
From good to great CDO
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The evolving CDO role will challenge structure, scope and power
relationships between executive committee members.
The scarcity of information leader talent will require executive
leaders to develop it as much as hire it.
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At the end, on Big Data, a CDO and the
team should
• Support the data initiatives, using the assets from
different sources, with quality as a requirement
• Drive business insights, so the users can act
promptly
• Execute his/her tasks fast, in real-time if possible
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The main drivers for
Data/Big Data projects
• Make more money
• Reduce current costs
• Improve efficiency
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What it takes to make Big Data projects
drive results
• Data – understand what they have and
how to be creative when it comes to
using internal and external data
• Models – focus on developing models
that predict and optimize
• People – transform their organizations
with tools and effective training so that
managers can take advantage of Big
Data's insights.
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To start an Analytics Team inside, there are 4
main things to consider
People
Technology
Process to
implement the
Practice
Methodology for
the Delivery
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From good to great, an analytics team
must have:
• Passion for analytics and data
• Never stop learning
• Always be there for tough analytics
questions
• Ask questions until everything makes sense
and you are satisfied with the answers and
analyses
• Learn how to develop prototypes quickly
• Be an advocate for building a strong
foundation in corporate analytics
• Be a "bridge builder" between IT and
business users
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Which companies will thrive in 2015?
• The ones which will understand how to adapt faster to
this new scenario
• The ones which will have successful Analytics
implementations
• The ones with great human capital, which understand
how to leverage their resources and with proven
methodologies to embrace this change
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Is your company going to lead,
influence or follow when using data
and analytics to drive results ?
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Major points on how to structure
a data governance program
• Upper management buying and support
• Do not reinvent the wheel : use and abuse of best
practices that already exist
• Communicate always and be transparent
• Quick wins
And …
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“Successful people shoot for the stars,
put their hearts on the line in every
battle, and ultimately discover that the
lessons learned from the pursuit of
excellence mean much more than the
immediate trophies and glory”
Josh Waitzkin, The Art of Learning
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Thank you
Mario Faria
Data Strategy Advisor
http://www.linkedin.com/in/mariofaria/
Founder of the Digital Mad Men
www.slideshare.com/fariamario
Twitter : @mariofaria
fariamario@hotmail.com
+1 (425) 628-3517