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
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.
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.
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
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
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
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
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.
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.
This introduction to data governance presentation covers the inter-related DM foundational disciplines (Data Integration / DWH, Business Intelligence and Data Governance). Some of the pitfalls and success factors for data governance.
• IM Foundational Disciplines
• Cross-functional Workflow Exchange
• Key Objectives of the Data Governance Framework
• Components of a Data Governance Framework
• Key Roles in Data Governance
• Data Governance Committee (DGC)
• 4 Data Governance Policy Areas
• 3 Challenges to Implementing Data Governance
• Data Governance Success Factors
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
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
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.
This presentation was part of the IDS Webinar on Data Governance. It gives a brief overview of the history on Data Governance, describes how governing data has to be further developed in the era of business and data ecosystems, and outlines the contribution of the International Data Spaces Association on the topic.
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.
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.
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.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
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.
Convincing Stakeholders Data Governance Is EssentialDATAVERSITY
Organizations are investing heavily in becoming data-centric. Data Governance practitioners must begin to deploy effective Data Governance techniques to support these investments. One of these techniques is to tackle the problem of convincing stakeholders that Data Governance is necessary. This webinar will help you address that challenge.
Join Bob Seiner for this RWDG webinar, where he will provide three questions that must be answered thoroughly and honestly from a business and technical perspective. The answers to these questions will provide practitioners with the artillery needed to break down barriers preventing the organization from being convinced that the time is right to formalize Data Governance.
This webinar will focus on:
- Identifying the stakeholders that must be convinced
- The three questions that must be asked of the stakeholders
- What answers you should expect to receive
- The answers that may surprise you
- Using the answers to convince stakeholders that Data Governance is necessary
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
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.
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.
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.
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 Governance and Metadata ManagementDATAVERSITY
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
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
You Need a Data Catalog. Do You Know Why?Precisely
Data catalog has become a more popular discussion topic within data management and data governance circles. “What is it?” and “Do I need one?” are two common questions; along with “How does a catalog relate to and support the data governance program?”
The data catalog plays a key role in the governance process; How well information can be managed, aligned to business objectives and monetized depends in great part to what you know about your data.
In this webinar you will learn about:
- The role of the data catalog
- What kinds of information should be in your data catalog
- Those catalog items that can be harvested systemically versus those that require stewardship involvement
- The role of the catalog in your data quality program
We hope you’ll join this on-demand webinar and learn how a data catalog should be part of your governance and data quality program!
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.
This presentation was part of the IDS Webinar on Data Governance. It gives a brief overview of the history on Data Governance, describes how governing data has to be further developed in the era of business and data ecosystems, and outlines the contribution of the International Data Spaces Association on the topic.
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.
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.
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.
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
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.
Convincing Stakeholders Data Governance Is EssentialDATAVERSITY
Organizations are investing heavily in becoming data-centric. Data Governance practitioners must begin to deploy effective Data Governance techniques to support these investments. One of these techniques is to tackle the problem of convincing stakeholders that Data Governance is necessary. This webinar will help you address that challenge.
Join Bob Seiner for this RWDG webinar, where he will provide three questions that must be answered thoroughly and honestly from a business and technical perspective. The answers to these questions will provide practitioners with the artillery needed to break down barriers preventing the organization from being convinced that the time is right to formalize Data Governance.
This webinar will focus on:
- Identifying the stakeholders that must be convinced
- The three questions that must be asked of the stakeholders
- What answers you should expect to receive
- The answers that may surprise you
- Using the answers to convince stakeholders that Data Governance is necessary
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
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.
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.
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.
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 Governance and Metadata ManagementDATAVERSITY
Metadata is a tool that improves data understanding, builds end-user confidence, and improves the return on investment in every asset associated with becoming a data-centric organization. Metadata’s use has expanded beyond “data about data” to cover every phase of data analytics, protection, and quality improvement. Data Governance and metadata are connected at the hip in every way possible. As the song goes, “You can’t have one without the other.”
In this RWDG webinar, Bob Seiner will provide a way to renew your energy by focusing on the valuable asset that can make or break your Data Governance program’s success. The truth is metadata is already inherent in your data environment, and it can be leveraged by making it available to all levels of the organization. At issue is finding the most appropriate ways to leverage and share metadata to improve data value and protection.
Throughout this webinar, Bob will share information about:
- Delivering an improved definition of metadata
- Communicating the relationship between successful governance and metadata
- Getting your business community to embrace the need for metadata
- Determining the metadata that will provide the most bang for your bucks
- The importance of Metadata Management to becoming data-centric
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
You Need a Data Catalog. Do You Know Why?Precisely
Data catalog has become a more popular discussion topic within data management and data governance circles. “What is it?” and “Do I need one?” are two common questions; along with “How does a catalog relate to and support the data governance program?”
The data catalog plays a key role in the governance process; How well information can be managed, aligned to business objectives and monetized depends in great part to what you know about your data.
In this webinar you will learn about:
- The role of the data catalog
- What kinds of information should be in your data catalog
- Those catalog items that can be harvested systemically versus those that require stewardship involvement
- The role of the catalog in your data quality program
We hope you’ll join this on-demand webinar and learn how a data catalog should be part of your governance and data quality program!
RWDG Webinar: Achieving Data Quality Through Data GovernanceDATAVERSITY
Data quality requires sustained discipline around the management of data definition and production. Data Governance is a large part of that discipline. The relationship between how well data is governed and the quality of the data is obvious. You cannot have high quality data without active Data Governance.
This month’s Real-World Data Governance webinar with Bob Seiner addresses how to improve data quality through the application of Data Governance practices. Quality starts with a plan and requires formal execution and enforcement of authority over the data. Attend this webinar and take away a plan to achieve data quality through Data Governance.
In this webinar, Bob will discuss:
• How Data Governance leads to data quality
• Core principles of Data Governance and data quality success
• Quality metrics based on governance practices
• Relationship between quality and governance roles
• Steps to achieve quality through governance
Managing for Effective Data Governance: workshop for DQ Asia Pacific Congress...Alan D. Duncan
This session reflects on the human aspects of Data Governance and examines what it takes to be successful in implementing effective information-enabled business transformation:
* Do we need to rethink our Data Governance strategies?
* Is enterprise-wide Data Management & Governance really achievable?
* What techniques and capabilities do we need to focus on?
* What skills and personal attributes does a Data Governance Manager need?
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
Finding the perfect data governance environment is an elusive target. It’s important to govern to the least extent necessary in order to achieve the greatest common good. With the three data governance cultures, authoritarian, tribal, and democratic, the latter is best for a balanced, productive governance strategy.
The Triple Aim of data governance is: 1) ensuring data quality, 2) building data literacy, and 3) maximizing data exploitation for the organization’s benefit. The overall strategy should be guided by these three principles under the guidance of the data governance committee.
Data governance committees need to be sponsored at the executive board and leadership level, with supporting roles defined for data stewards, data architects, database and systems administrators, and data analysts. Data governance committees need to avoid the most common failure modes: wandering, technical overkill, political infighting, and bureaucratic red tape.
Healthcare organizations that are undergoing analytics adoption will also go through six phases of data governance including: 1) establishing the tone for becoming a data-driven organization, 2) providing access to data, 3) establishing data stewards, 4) establishing a data quality program, 5) exploiting data for the benefit of the organization, 6) the strategic acquisition of data to benefit the organization.
As U.S. healthcare moves into its next stage of evolution, the organizations that will survive and thrive will be those who most effectively acquire, analyze, and utilize their data to its fullest extent. Such is the mission of data governance.
Real-World Data Governance: Data Governance Roles & ResponsibilitiesDATAVERSITY
Well thought out data governance roles and responsibilities lie at the heart of successful data governance programs. All activities focus on the roles. From how we recognize stewards and apply governance, to how we engage and communicate with the people in the roles – the roles become the operating model for how governance works.
Join Bob Seiner for this month’s installment of the DATAVERSITY Real-World Data Governance webinar series focused on defining an operating model that can be assimilated to your organization. This model includes an easy-to-explain set of roles and responsibilities aligned with how your organization functions.
The session will cover:
Operational, Tactical, Strategic and Support Roles
How to recognize your stewards and other roles
How to apply roles consistently through all facets of your program
Providing incentive for active involvement
There are plenty of office etiquette lessons every employee should be cognizant of. From spreading too much gossip to talking too loudly around other co-workers, there are a host of mistakes that do nothing more than slow down everyone's day. See which mistakes made the list and what you can do to keep them from happening at your company.
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Updated with revised DMBoK 2 release date
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5. GMAC background
• 2006 GMAC ResCap was formed
• GMAC’s Residential Mortgage business
• Merger of two like-sized companies:
– GMAC Residential Funding Corporation (GMAC-RFC)
– GMAC Residential Mortgage
5
6. GMAC background
• Merger necessitated the integration of two like-sized,
independent entities
• Different people, processes, and technology
• Each company had its own separate and distinct systems:
– Lending
– Servicing
– Capital markets
– General Ledger
– HR
– Data Warehouses
– Etc.
• There was a need to integrate the data of the two organizations
– Our Data Services organization was created to address this need
6
7. Why Data Governance?
• Gartner estimates that organizations spend at least
70% percent of their BI budgets to resolve issues
related to people, process, and governance
• "Due to a lack of a cohesive strategy, many
organizations have created multiple, uncoordinated
and tactical BI implementations, which has resulted in
silos of technology, skills, processes and people."
– Betsy Burton, VP and distinguished analyst at Gartner
7
8. Importance of Data to Financial
Services
• Two sustaining elements for a Financial Services
company:
1. Information
2. Access to Capital
• GMAC rated Data Integrity as Top Priority in an
Executive Survey
8
11. Dramatic consequences
June 03, 2003 TORONTO (Reuters) - Fannie Mae, which finances home mortgages,
TransAlta Corp. said on Tuesday it will take a stated in a news release of third-quarter
$24 million charge to earnings after a bidding financials that it had discovered a $1.136
snafu landed it more U.S. power transmission billion error in total shareholder equity. Jayne
hedging contracts than it bargained for, at Shontell, Fannie Mae senior vice president for
higher prices than it wanted to pay. investor relations, explained in a written
[...] the company's computer spreadsheet statement, "There were honest mistakes made
contained mismatched bids for the contracts, it in a spreadsheet used in the implementation of
said. "It was literally a cut-and-paste error in an a new accounting standard."
Excel spreadsheet that we did not detect when —From PC World
we did our final sorting and ranking bids prior
to submission," TransAlta chief executive Steve
Snyder said in a conference call. "I am clearly
disappointed over this event. The important
thing is to learn from it, which we've done."
11
12. Data Issues get worse during an M&A
#53
Homecomings / #24 - IMS-R DW Data Finance
#4 & 50 - 1st & HE E-Commerce
Retail NC Loan Info Master #25 Valuation
ADI #4 & 50 1st Servicing #33 RVA/RIF
MortgageFlex #34
Master
& HE NC
Loan Info Other Servicing
Correspondent #1 - 1st & HE #28 Apps
Loan Info IMS-R HIP
#20 - 1st & HE Data
Café 4.0
Servicing Data
Café 2.2 #35 Café 2.2 Data
IMS-R
Capital Markets #27
AssetWise #2 & 16 - 1st & HE #26 Servicing
Servicing Data RFC
#14 & 15 – IMS-R SBO SBO #30
#42 - 1st Loan Info
DRAFT
Café 2.2 Data
(specific products ) #3 & 49 - 1st & HE
May go through ADI IMS-R #31
NC Loan Info
Café 4.0
#44 - IMS-R Data
Data Warehouse /
Institutional ODS/Vision #29
#1 - 1st & HE Loan Info Automated Pooling
Café 4.0
Finance
#18 Café 2.2 st
#48
IMS-R #2 & 16 - 1 & HE Commitment #37 Manual
Conforming Gate
Loan Info Servicing Info Interface
AssetWise Data #32
(Manual) #22
Commitment
Homecomings / Management
Broker Finance #23
Asset Lock #51
MortgageFlex #19 - 1st & HE Conforming Loan #11
Bid Commit PeopleSoft
1st & HE Servicing Data #52 #43
Middleware /Business App #36
#42 - 1st & HE Loan Info
st
1 & HE Servicing Data Common Loan Interface #6 - 1st & HE
#54 (CLI) Servicing
General Data #13 - Summary
Ledger Entries
#47 Ledger
1st & HE #9 - 1st & HE
Correspondent Loan Loan Info GLS
Direct/Ditech #5 - 1st & HE Loan Info Info
#21- Finance
WALT 1st & HE Servicing Data #8 - Loan Updates Detailed
Eclipse Engenious Ledger SmartStream
Engenious Middleware Entry
Capital Markets #46 Contract ID
Sales & File
Resi Lookup
Switch #10 - 1st & HE Switch Service
Retail Loan Info CMS
#41 - HE Loan Info
CoPilot #7 - Daily
Back #45- Contract
Retail Interface ID Lookup
#40 - 1st & HE Loan Info Request
Pilot
Lendscape st
#39 - 1 & HE Servicing Data Servicing
#12
#38 - HE Servicing Data MortgageServ (LOIS, NELI)
12
13. GMAC ResCap Data Program – July 2006
Residential Finance Group: Importance versus Effectiveness Gap -
5.0 Jul
Key Strengths y
High Priorities
20
06
Strategy and Planning
Survey concluded
that Data is of high
Enterprise Architecture
Availability Management
Security Policies and Stds
Data and Knowledge Mgmt importance and that
it was ineffectively
Importance
Portfolio Management
4.0 Project Mgmt and Execution
IT Staff Development Value Demonstration
managed.
Application Design Leadership Development
Business Case Discipline
Risk Management Disaster Recovery and BCP
Requirements Definition Process Digitization
Performance Management IT-Enabled Collaboration
Technology Innovation
Performance Reporting Life-Cycle Cost Efficiency
Maint. Cost Containment
Cost Transparency
Vendor Perf Oversight
Potentially Over Opportunistic
Allocated Improvement
Vendor Segmentation
3.0
0.00 1.00
Effectiveness Gap = Importance - Effectiveness
Governance Performance Measurement and Value Demonstration
Security and Business Continuity Planning Infrastructure Delivery and Management ----- Importance Ave: 3.82
Applications Delivery and Management Vendor Management ----- Company Gap Ave: 0.67
Talent Management Business Enablement
13
14. GMAC ResCap Data Program – July 2007
Residential Finance Group: Importance versus Effectiveness Gap - July 2007
7.0
Key Strengths High Priorities
6.5
Availability Management
Strategy and Planning
6.0 Business Continuity Planning
Business Responsiveness Project Delivery
Partner Requirements Definition
End-User Support Business Liaison
Importance Financial Impact
Security Technical Skills
Technology Provisioning Skills Adaptation
Leadership Skills
5.5 Risk Management Business Case Achievement
Data and Knowledge Management System Adoption
Value Demonstration
Business Skills
Prioritization Discipline Business Functionality
5.0 Business Case Discipline Communication
Project Skills Cost Transparency
Technology Innovation
Vendor Alignment
Opportunistic
User Training
Low ROI Improvement
4.5
(0.8) (0.3) 0.3 0.8
ResCap-RFG Average
Effectiveness Gap = Business Partner Importance - Business Partner Effectiveness
Benchmark Average
14
16. Strategic Data Initiative - Approach
Step #1 – Get sponsorship from the top
It’s easier to get everyone marching in the same direction when it
comes from the top
Try for the CEO – if that doesn’t work the CFO and COO are your best
bets
16
17. Strategic Data Initiative - Approach
Step #2 – Focus on Culture during an M&A
Collaborated with a team of Business and IT stakeholders to build SDI
Performed a cultural assessment:
- Human Synergistics OCI
- Competing Value’s Framework
17
18. Strategic Data Initiative - Approach
Step #3 – We took a “Best of Both Worlds” (or Reese’s) approach
- Assessed components of both the RFC and RESI data programs
- Used strengths from each one and sought to enhance them
- Where neither was strong brought in outside help
- Your situation may vary – it may make more sense to take an acquisition
approach
18
19. Strategic Data Initiative - Mission
“The people, process, standards, tools, and
procedures that develop a long-term
organizational framework and foundation
enabling ResCap to manage data as a
strategic asset, that will be used as a
trusted source of information across
the Enterprise.”
19
20. Strategic Data Initiative -
Deliverables
• SDI had three major deliverables:
– Establish an Enterprise Data Governance organization
– Establish an Enterprise Data Stewardship organization
– Establish an IT Data Services organization
Data
Steering Governance
Committee
Working
Group
Minimum
Data
Data
Quality
Standards
Meta-Data
Management
Enterprise Enterprise
Stewardship Architecture
Business Unit SDI Data
Stewardship Services
Data
Data Sharing Data
Stewardship Architecture
20
21. SDI – IT Data Services Org
Data
• Data Governance Steering Governance
Committee
• Data Stewardship Working
Group
• Data Architecture Data
Minimum
Data
Quality
• Data Reporting Meta-Data
Standards
Management
• Data Integration Enterprise Enterprise
Stewardship Architecture
• Database Administration Business Unit SDI Data
Stewardship Services
• Project Management Data Data
Sharing Data
Stewardship Architecture
• Consulting
• Training
• Vendor Management
21
22. SDI – Data Architecture
• Data Architecture
– Consulting
– Data Modeling
– Data Analysis
– Data Quality processes &
standards
– Data Security
– Data Standards
– Tool Standards
– External standards bodies
(MISMO, XBRL, HL7, etc.)
22
23. SDI – Data Stewardship Model
Data
Steering Governance
Committee
DATA GOVERNANCE
Working
Data Governance Steering Committee (DGSC) Group
Data
Governance Minimum
Data
Roles Data
Data Governance Working Group (DGWG) Quality
Standards
Meta-Data
Management
Enterprise Enterprise
Enterprise Data Stewardship Office (EDSO) Stewardship Architecture
Enterprise
Data Stewardship Business Unit SDI Data
Roles Program Manager Program Staff
Stewardship Services
Data
Data Sharing Data
Stewardship Architecture
Business Units Data Stewards
(BUDS)
Business Unit
Business Unit Data Steward Manager
Business Unit Data Steward Manager
Business Unit
Data Stewardship Data Steward Manager
Roles
Definer Producer User
Definer Producer User
Definer Producer User
Note: Business Units may choose to assign one or more associates to fulfill the different data
stewardship roles within the business unit
.
23
24. Data Governance
Data Governance at GMAC ResCap
– Executes and enforces authority over the management of data assets through
Data Quality, Stewardship, and Standards initiatives
– Empowers an organization to define guiding principles, policies, processes,
standards and technologies
– Ensures the quality, consistency, accuracy, availability, accessibility, and audit-
ability of GMAC’ s data
In order to:
– Support sustainable growth Data
– Improve investor and client satisfaction Steering Governance
Committee
– Provide disciplined leadership Working
Group
– Manage and reduce risk
Minimum
– Streamline operations and improve time to market Data
Quality
Data
Standards
Meta-Data
Management
Enterprise Enterprise
Stewardship Architecture
Business Unit SDI Data
Stewardship Services
Data
Data Sharing Data
Stewardship Architecture
24
26. Data Governance Purpose
Improve productivity and lower cost of operations by:
– Approves, sponsors, and prioritizes all Enterprise Data projects
– Managing data so that it is available, complete, timely, and accurate
– Defining and enforcing data quality and data integrity standards
– Identifying and promoting standard tools and data quality standards
Improve risk posture by:
– Establishing data stewardship throughout the organization
– Implementing an effective process for escalating, prioritizing, tracking, solving and reporting on
enterprise data risk issues
– Establishing rules governing the lifecycle of data
– Identifying and utilizing standard tools and access policies to allow for authorized and verified
access to data
Improve organizational effectiveness through
– Measuring the effectiveness of Data Governance and its alignment to corporate goals
– Assumes ownership of all Enterprise Data
– Owns the Enterprise Data Warehouse and Enterprise Data Repository
– Resolves disputes regarding data issues
– Manages data quality
26
27. Data Governance Organization
Steering Committee
– Made up of Senior Business leaders
– Maintains ultimate accountability for all facets of Data Governance
– Establishes the Working Group to achieve the Data Governance goals and
objectives
– Reviews results of the Working Group on a regular basis
– Meets monthly
Working Group
– Two or more business data SME’ s from each business area
– Appointed by the Steering Committee member to achieve the Data
Governance goals and objectives
– Strives to build consensus across organizational boundaries
– Escalates issues to Steering Committee when appropriate
– Meets weekly or more frequently if necessary
27
29. Organization Membership
Steering Committee
– One Chairperson
– One senior manager from each business group in ResCap
– Chairperson for the committee is appointed by the Executive Committee and
position is reviewed annually
– IT only has one seat – the CIO; all others are business people
Working Group
– Facilitator plus one or more representatives for each Steering Committee
member
– Facilitator for the Working Group is appointed by the Steering Committee
– Representatives appointed by Steering Committee Member for their business
group
– Recognized as experts or SMEs in their line of business
– Many are also Data Stewards for their business area
29
30. Roles and Responsibilities
Steering Committee Chair
– Establishes agendas, leads meetings and records results
– Facilitates votes on business before the Committee
Steering Committee Member
– Ensures effective utilization of the program throughout ResCap
– Votes on business before the Committee, either in person or via proxy
– Appoints Working Group representative(s)
– Works with Working Group representatives and other Steering Committee
Members to gauge progress and resolve issues related to Data Governance
goals and objectives
30
31. Roles and Responsibilities
Working Group Facilitator
– Establishes agendas, leads meetings and records results
– Works to build consensus and arbitrate disputes
– Manages voting process
– Escalates issues to the Steering Committee when appropriate
Working Group Member
– Effectively represents views of their business or support unit as well as
understands the views and needs of the enterprise
– Implements programs and participates in projects to achieve the Data
Governance goals and objectives
– Directs metadata requirements
31
32. Working Group Member Profile
• Effectively represent the views of their business or support unit
• Communicate the policies, standards and decisions of the Data Governance
Organization to their organization
• Implement programs and participate in projects to achieve the Data
Governance goals and objectives
• Work to define data in the best interest of the organization,
• Act as an advocate for Data Governance and effective corporate-wide data
management
• Exercise authority for making decisions regarding data and related policies.
32
33. Working Group Member Attributes
• Understanding of the Mortgage Business in general and a strong
understanding of their Business/Support unit
• Understanding of the scope and location of the data within their business
area, and relationships to other business areas
• Strong knowledge of data attributes, their source, usage, and definition
• Knowledgeable of the strengths and weaknesses of data as it exists within
the business unit
• Demonstrated ability to work on a team
33
34. Working Group Member Workload
• Workload – 2 to 3 hours per week
• Communications and Execution – WG representatives are the Steering
Committee member’s link to the Working Group
• Coverage – Provide adequate representation for your organization
(more than one representative allowed)
• Teamwork – A business area must work as a unit
• Attendance – Primaries and backups should be assigned. Attendance
is tracked and published.
• Performance – Individuals are responsible for active participation in the
Working Group, and must have performance goals for Data
Governance activities.
34
35. Decision-making
The Steering Committee operates by simple majority vote of full
membership
– At least 75% representation (through attendance or proxy) is required for
quorum
– Voting can only take place if quorum is achieved
– Chairperson has voting and veto privileges
– Decisions can result in approval, conditional approval, rejection, rejection
with request for follow-up, or refer to Executive Committee
– Decisions can be appealed by the Steering Committee Member to their
Executive Committee representative, who can choose to bring the matter to
the Executive Committee for consideration
35
36. Decision-making
The Working Group operates by consensus – 100% concurrence
is required for approval
– Each organization has one vote, regardless of the number of representatives
– Facilitator has no voting privileges
– The group works to define the problem so the decision can result in
approved by consensus, rejected with a request to return with additional
information, rejected as presented, or escalated to the Steering Committee
36
37. Data Governance
Accomplishments
• Enterprise Data Model
– Modified a generic Industry data model to accurately represent our business
• Data Quality
– Identified issues with certain calculations in a source system; reviewed with Credit
Policy & Capital Markets; clarified business rules for calcs; source system modified
to conform to business rules.
– Initiated a pilot of the Larry English TIQM data quality methodology.
• Data Survivorship
– Determined the correct System of Record for 572 data elements in the EDR that
could be sourced from either the Origination or Servicing system. In some
instances both records were stored for historical purposes.
• Data Security
– Classified the GMAC Proprietary data elements in the EDR. These are stored in
the Metadata tool and reports which contain these data elements contain a “GMAC
Proprietary” footer.
• Data Mart project reviews
– Reviewed designs of multiple data mart projects
37
38. Data Governance
Accomplishments
• MISMO support
– Ensure that Enterprise data conforms to MISMO XML standards
– Actively participate in MISMO Governance
• GMAC ResCap Integration Project
– Documented the current state data stores and data flows for the Enterprise
– Identified the data requirements for all the Data Consumers – ~7,000 data
elements
– Consolidated these data requirements – eliminating dupes and conforming names
- ~3,500 data elements
– Reviewed the data needs among the Data Producers to optimize builds of
interfaces
– Developed a scorecard (13 questions) to determine what data is strategic
– Strategic data to be hosted in Enterprise Data Repository
• Enterprise Data Repository (EDR)
– Single Source of Truth for our Enterprise Data
– Used to build functional data marts
– Owned and maintained by Data Governance group
38
39. Developed Data Architecture
Rules
• Enterprise Data Architecture Rules
Data is owned by the Data is adjudicated by
corporation Data Governance
Data is managed by Data is structured and
data stewardship stored based on its
behavior and usage
Data is shared and Data is not duplicated
accessed using unless duplication is
common methods necessary
Data is secured Meta data is maintained
Data is modeled using Data is managed using
naming conventions approved standards and
and standards tools
39 39
40. Consolidated Business Data
Requirements
• Output
– Normalized business data requirements from
~7000 elements to ~3500 elements
• Benefits
– Provided data producers a de-duped listing from
which to work
– Provided data producers a single list of consumer
data needs so they can determine how to expand
their platforms
40 40
41. Scored Enterprise Strategic Data
• What
– Score the consolidated list using criteria
developed by the Data Governance Working
Group
• Why
– Define candidate list of data elements for EDR
– Develop one drop-off point for sharing data with other business units rather
than developing many point-to-point ones between them
– Eliminate any subsequent work for producers to address needs for new
consumers
– Sharing data in this way follows many of the enterprise data architecture
rules defined by the Data Governance Working Group
41 41
42. Enterprise Data Repository (EDR)
Lending Data (current data)
LendScape CFP
• Ten data sources (NetOxygen)
Retail
• Target is Enterprise Data (Pilot)
Repository (EDR) – all data elements Retail HEQ
(Co-Pilot)
will be conformed & cleansed. Ditech / Direct ETL Processing
(Eclipse/LPM)
• Single version of the truth for our Wholesale EDAP
(WALT) Enterprise Data Repository
Enterprise data Business Specific
Data Marts
• Data marts will be built from EDR
Lending Data EDR
(historical loads) - Extraction
- Transformation
Retail - Loading into ODS
• Enterprise Data Model used to Customer / Borrower Business Lending LendScape
(Pilot Archive) - Data cleansing
- Meta data Product / Loan
design EDR
Property
Retail
Servicing
(Co-Pilot)
Risk Management ECR
• 3NF Ditech
(Eclipse)
• Data Governance “owns” EDR Wholesale
(WALT / EDAP)
• 808 data elements to start
Servicing Data
• ~800 more being added for NC MortgageServ
Other Data
Credit
Excelis
(historical)
Shaw
(historical) Business Objects
SAS Reports
Reports
42
43. Developed charge-back model
2007 ISCO BU Name Total Allocation Total Percent
Admin Overhead and Other Ops $ 772.50 0.70%
Automated Decisioning $ 25.43 0.02%
CFO Office $ 8,100.41 7.33%
Construction Lending $ 84.75 0.08%
Consumer Lending Admin $ 11,975.62 10.84%
Corporate Real Estate $ 101.70 0.09%
Correspondent Funding $ 18,002.86 16.30%
Ditech $ 14,656.39 13.27%
EDAP Services ESDO
ISCO $ 1,249.78 1.13%
ESG Fee Based Servicing $ 2,203.61 1.99%
Strategic Business Unit Consumer Lending Admin ESG Owned Servicing $ 30,696.58 27.79%
Reporting Period April, 2007 Financial Services $ 3,992.11 3.61%
GHS Mortgage $ 118.66 0.11%
GHS Other - Admin $ 101.70 0.09%
Metric % of Total $ Allocation
GHS RE Co-Owned $ 2,911.31 2.64%
Data Mart Hosting (MB) 127,146,944 12.25% $ 708.63
GHS RE Franchise $ 16.95 0.02%
Business Objects Usage (# Users) 23 0.60% $ GHS Relocation
69.27 $ 3,043.21 2.75%
Home Connects $ 853.78 0.77%
Business Objects Hosting (MB) 78 0.61% $ 73.55
Home Solutions Svg Cross Sell $ 42.38 0.04%
DataStage Usage (Seconds) 2,115,824 17.63% $ 2,284.21
Human Resources $ 16.95 0.02%
DataStage Hosting (MB) 324,604 10.19% $ Investment Banking - Cap Markets $
1,119.85 1,792.14 1.62%
IT Lendscape $ 1,658.23 1.50%
Enterprise Allocation $ 1,530.63
Operational Risk Management $ 668.90 0.61%
Base Support (Hours) 79 10.84% $ 6,189.48
Retail Network Summary $ 6,941.79 6.28%
Total 10.84% $ Retention
11,975.62 $ 305.11 0.28%
Strategic Sourcing $ 127.13 0.12%
Voice of the Customer $ 8.48 0.01%
Warehouse and Finance Solutions $ - 0.00%
Services: ECR Data Mart, Business Objects Universe, Business Objects Accounts $ 110,468.46 100.00%
43
45. Lessons Learned
1. Obtain Senior Executive (CEO if possible)
sponsorship for Data Governance
2. Can not underestimate the importance of Culture
3. Choose an approach to merging your Data
programs
4. Need a clearly defined strategic mission and
program to transform the way you manage data
5. Consolidate Data Architecture & Delivery services
– create a single point of accountability for IT Data
Delivery in your organization
45
46. Potential pit-falls
1. Changes to Executive staff during M&A can derail
Data Governance continuity
2. Management Consulting companies don’t know
your company as well as you do
3. Data Governance can be perceived as
bureaucratic
46
47. Where to go for more information
• The Data Warehousing Institute (TDWI)
– http://www.tdwi.org/index.aspx
• Data Management Association (DAMA)
– http://dama.org/
• DM Review magazine
– http://www.dmreview.com/
• MDM Institute
– http://www.tcdii.com/index.html
• The Data Administration Newsletter (TDAN)
– http://www.tdan.com/
47
49. Contact Information
• If you have further questions or comments:
Rob Lux
CTO, GMAC ResCap
rob.lux@gmacrescap.com
215-734-4205
www.mortgagecto.org
49