T3: Integrating Data Governance and Data Modeling into Your SDLC

How do I integrate Data Governance activities into an SDLC? Why do certain types of projects stall (or worse, fail!) when we get to the “model the data” step, and how can that be avoided? What personal skills can I practice so I’m better equipped to deal with the conflict, power-plays, and politics surrounding some kinds of governance and architecture decisions?

A Data Governance pioneer and the best-selling author of The Data Model Resource Book series collaborate to provide answers to these questions in a business-meets-fun environment. Participants learn left-brain, just-the-facts business practices, and also get to practice right-brain exercises designed to get to the human dynamics at the root of many data-related conflicts. Participants leave with a methodology for aligning SDLCs, Data Governance activities, and pre-modeling steps designed to manage enterprise risk. They also leave with a framework for dealing with the human side of negotiating these steps.

Participants will:

• Learn key Data Governance steps and a methodology for fitting them into an SDLC
• Learn Data Modeling risk factors and how to work with your Project Management Office to manage those risks
• Learn about core principles and dynamics dealing with gaining funding, keeping momentum, showing value, understanding what is happening politically, and effectively collaborating
• Hear stories about how other organizations have dealt with data-related conflict
• Practice exercises to deal with people-based conflict

Gwen Thomas is President of The Data Governance Institute, which provides publications, training, and consulting in the areas of data governance, stewardship, compliance, and data strategies.

Gwen has designed Data Governance programs or helped existing programs become more mature at companies such Washington Mutual, Russell Investments, Sallie Mae, NDCHealth/Wolters Kluwer, Wachovia Banks, Disney, and Coors. She has provided strategy and advice to many other public, private, and governmental organizations, often partnering with groups such as IBM and systems integrator CIBER, for whom she designed their Sarbanes-Oxley practice. She has worked with a series of large and mid-sized organizations to reduce risk in data integration, warehouse, metadata, web portals, master data, and content projects.

Publisher of www.DataGovernance.com, the web’s largest collection of vendor-neutral Data Governance information and humor, Gwen is a frequent presenter at industry data events and contributor to IT and business publications. She is also author of the book Alpha Males and Data Disasters: The Case for Data Governance.

Len Silverston is a consultant, author, and speaker with over 25 years of experience helping organizations integrate their information and systems. Mr. Silverston is a thought leader in the fields of data modeling, data management, and in the human dynamics of integrating data. He has been a pioneer in the field, most notably by developing an extensive library of “Universal Data Models,” or in other words, re-usable models, that he has used to help a great deal of organizations develop data models in much less time with much greater quality. He is the best-selling author of The Data Model Resource Book series, which describe over 230 reusable, holistic data models and which was rated #12 on the Computer Literacy Best Seller List.

Mr. Silverston has published numerous articles and has been a frequently invited speaker at many international conferences talking on subjects ranging from re-usable models to politics, power, and culture in data management. His latest book, The Data Model Resource Book, Volume 2, which provides universal data models for various industries, has been translated into Chinese. He is the winner of the DAMA (Data Administration Management Association) International Professional Achievement Award for 2004 and the DAMA Community Award for 2006.

Mr. Silverston's company, Universal Data Models, provides consulting, training, publications, and software regarding re-usable data models and data management strategies to help integrate information, systems, and people.