DAMA + Wilshire Meta-Data Conference - Data Strategy Track
Every organization has a base set of knowledge about its data. Every organization has people that know (or were involved in) the data’s definition, production and/or usage. These same people know how to use the data and know the issues around the data. Every organization maintains key operational and decision support data through some type of process and methodology. But not every organization governs and stewards its data.

This three-hour session from Bob Seiner focuses on building Data Governance and Data Stewardship Programs that fit over an organization’s existing foundation of people, data and process. The session provides best practices and an organizational framework that values and leverages existing structure while addressing opportunities to improve. This “Non-Invasive” approach sets attainable business and technology expectations and can be completed incrementally and/or through orientation to other key data initiatives such as Business Intelligence, MDM, DQM, ERP package implementations and Meta-Data Management.

This session will focus on:
  • Developing a Data Governance Organization and Governance Support Organization
  • Overlaying Existing Methodologies with Data Governance and Stewardship Discipline
  • Identifying and Mentoring the Appropriate Domain and Operational Data Stewards
  • Defining and Managing Cross-Business Unit and Functional Area Domains of Data
  • Developing Data Governance Tools and Measuring Business Value and Acceptability
  • Improving Data Awareness and Promoting Data Governance Communications
The new heighten interest in Information Governance, having the proper information stewardship and control functions in place, has elevated the awareness of organizations of having the appropriate Information Resource Management in place. The business environment demands an Information Management function with a focus on accountability and participation of business and information technology personnel alike. This participation must transcend the boundaries of applications, project scopes, and departments; organizations need an effective approach to facilitate this enterprise process.

The Data Certification Framework helps organizations control and leverage their information resource to achieve increased compliance, operational effectiveness and strategic positioning within their markets. Data Certification provides the processes, controls, roles, methods, tools and techniques required to accomplish these goals.

This tutorial provides the attendees with a full description of the Data Certification approach and how it helps your organization increase information management. Attendees will learn and practice valuable methods and techniques to enhance their effectiveness in Information Management; the tutorial includes exercises and examples of the associated tools and techniques for managing information across the enterprise.

Master data is a distinct class of data that must be managed well for data sharing, or exchange, to be successful within an enterprise. Failure to do so leads to well-known data quality problems that may severely limit data warehouses and linked transaction systems. This is because master data has its own unique properties and behaviors that require specific management techniques to be applied to it. General data management approaches are simply insufficient. This tutorial explains how to manage master data with the goal of making it an enterprise-wide data resource. Specific issues in master data management (MDM) are described along with techniques to solve them. Particular attention is paid to the metadata required to manage master data, the relationship between master data and data quality, and the strong link between data governance and master data. MDM is dealt with from the strategic level, e.g. building a business case, down to the technical level, e.g. data models that extend master data to include management metadata.

Participants will learn about:
  • The structure of master data, what sets it apart from other classes of data, and planning for its management.
  • Organizational requirements for successful MDM, including stewardship and governance.
  • Data architecture for master data, both at the enterprise level and the database design level
  • Metadata and repository functionality required to carry out common MDM tasks.
  • Current vendor approaches to providing solutions for MDM, and how to evaluate them.
As companies react to the rapidly changing regulatory environment and work to mitigate risk, audits have become a frequent tactic for monitoring compliance. Internal and external audits, as well as regulatory investigations, regardless of purpose, ask similar questions. Whether for SAS 70, Sarbanes-Oxley, or legal investigation, nearly every auditor within your organization seeks the same thing – metadata. But do those companies who spend thousands on audits place the same monetary value on metadata management? Drawing on nearly a decade of experience in the healthcare and financial sectors, Bill will not only help you learn ways to educate your organization about the value of metadata in an audit, but also how to find metadata that is already in the budget (one clue: it won’t be called metadata) and align your IT objectives with the organization’s business in an effective and mutual beneficial way.

Attendees will learn:
  • How auditors’ investigations relate to metadata management
  • Ways to demonstrate metadata’s cost-benefit to the audit process
  • Ways to adapt to the language and goals of the business without losing focus on metadata
  • How to learn from your executives what they already know about metadata
  • How to find hidden metadata initiatives in the budget and corporate initiatives
This session will begin by comparing and contrasting data governance and master data management and end with a demonstration of how applying data governance principles and standards, enables attaining the goals of master data management. This will be accomplished through a comparison of two case studies, whereby the companies have actively engaged in data governance and master data management initiatives for over 3 years.

Data Governance is important -- without the concept of a clear "owner" (or owners) of the data, decisions can rarely be made or enforced. At Wells Fargo, a series of committees was formed to define and enforce data governance, including stewardship of data elements, common business rules, and techniques for documentation and communication. In this presentation you will learn:
  • The organization structure needed to define and enforce governance
  • How to set up business data stewardship
  • The metadata structures needed to document data governance
  • How data governance made major projects go more smoothly
  • How data governance made it possible to define common business rules and get agreement to use them

Data departments are expected to support more than operational goals. They may be involved in enterprise-wide privacy, access management, governance, compliance, litigation, or risk management efforts. How do you keep track of the systems, data stores, and people involved in these efforts? This presentation demonstrates how to extend a typical metadata metamodel to store the information you need for these endeavors. We introduce six non-traditional metadata subject areas and demonstrate how they work together to meet operational and auditing requirements for risk-based \"Chains of Accountability.\" We learn how one company created and populated these subject areas in their metadata repository, and how they\'ve successfully used the results to help manage their Data Governance, Stewardship, Compliance, and eSecurity programs. Participants will learn:
  • How to describe typical data-related concerns using risk management terminology used by business, legal, compliance, and privacy.
  • The elements of six metadata subject areas (risk, risk management strategies, controls, permissions, roles, and accountabilities) used to support compliance and accountability
  • How to use metadata to translate typical data management efforts into compliant accountability chains.
  • How to gather metadata required to support those accountability chains and communicate value to the business.
“Data Governance” is top of mind for many corporate managers as the regulatory environment is becoming more rigorous. Businesses face mounting pressure to discover and protect hidden sensitive data elements, create master data repositories and reduce data inconsistencies across dataset boundaries. The first step for any of these kinds of data governance efforts is very basic: DISCOVERY: You can’t manage what you can’t find!

In the past, companies have attempted to use metadata to answer these questions. The problem is that metadata reflects what people assume is in their database…not the reality of what really exists. Learn how a new methodology called “data-driven mapping” and an accompanying technology eliminates the guesswork with a fact-based approach that efficiently examines millions of rows of data values to automatically discover hidden sensitive data, forgotten business rules and unknown data inconsistencies across disparate datasets. Customer case studies will include:
  • One of the world’s major credit card companies using this approach to quickly and affordably create an enterprise data flow map
  • One of the oldest and largest insurance companies identifying hidden sensitive data for de-identification prior to shipping overseas for outsourced development
  • the nation’s largest mutual fund company uncover forgotten business rules for a corporate master data management database.
Organizations in the early stages of SOA development face many challenges—governance is one of the most important. In order for SOAs to realize their intended business objectives—improved agility and reduced IT cost—organizations must always be in control of the services that are created, and then used and re-used. Governance that is implemented at design-time prevents an SOA from becoming simply ABOS—A Bunch of Services. Without proper design-time governance, services will be project-specific and redundant with other services. This will result in gaps across the business architecture, which increase IT costs and complexity without bringing any of the promised business benefits of SOA.

Brent Carlson, co-founder and vice president of technology at LogicLibrary, will explain how to initiate governance at the design and development phase and carry it through operations.

Carlson will
  • discuss the role of an integrated registry/repository in keeping IT properly aligned with high-level business processes
  • walk attendees through real-world success stories
  • address the return on investment many companies are now seeing – up to twenty-times their original investment – by properly managing software development metadata.

The BMO Financial Group views information as a strategic asset and should be managed with the same attention as human and capital resources. Numerous information management (IM) initiatives are underway to transform our Corporate Policy into implementable standards, practices and processes.

From the beginning, our work has been grounded in metadata management. This presentation shows how metadata and governance work together.
  • The landscape for governance and metadata management
  • How metadata, stewardship and governance work together
  • The value proposition for metadata management
  • How the data warehousing practice at BMO FG uses metadata

This case study explores the issues associated with developing a data standards program for establishing consensus and coordinating data exchange across an extended, multi-jurisdictional enterprise. One of the major challenges was the variation and disparity of data element formats, data types, and most importantly, definitions. The institution of a community-wide data standards governance program addressed these challenges, and in combination with an ISO/IEC 11179-based data standards registry, provides a single repository for managing the data standards process.

This presentation describes how Schneider implemented an ‘information stewardship’ approach to ensure information quality within and across business processes being redesigned. Experience how our organization learned that information is the glue that integrates business processes.
  • Where Information Stewardship fits within Business Process Redesign
  • Five phases (including deliverables) of Information Stewardship
  • Illustrate accomplishments in a real-life BPR effort
The illustration includes the old and new process, conceptual data model, information policies, required information quality levels, process life-cycle states among others. The business gained the ability to maintain satisfactory quality at the entity/attribute level. A real life example illustrates the redesign of our ‘Accept the Transportation Order’ process.

The Information Technology Infrastructure Library is a library of "best practices" for IT Service Management. While often associated with the operational side of IT management, it is also relevant to data architects and managers. ITIL practices such as Configuration, Change, and Capacity Management have direct implications for the practice of data management, while an ITIL initiative itself requires careful data architecture applied to the problem domain of information technology challenge faced also by metadata management. Come and learn all about ITIL from Charles Betz, the author of the newly published book "IT Service Management, Resource Planning, and Governance: Making Shoes for the Cobbler's Children (Morgan Kaufman/Elsevier, 2006). (please note: this is not an ITIL certification class)a Topics of the briefing will include:
  • ITIL and ITSM overview
  • How ITIL can assist the goals of Data and Metadata Management
  • How Data and Metadata Management may support an ITIL initiative
  • Configuration Management and Metadata Management: two sides of the same coin?
  • ITIL's limitations, challenges, and future prospects

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