Being able to consistently describe and name data in the enterprise is the most important step you can take towards achieving your data governance objectives. One of the biggest challenges in business is that companies don’t know what they’re talking about – literally. Key business metrics, business terms, data definitions, and how to translate data and information from one system to another are vaguely understood or understood in too many ways. Business data and facts are named obscurely, or redundantly, or with imprecision. As a business grows, changes, acquires, and divests operations, numerous opportunities appear to impact your business data in a detrimental way:

• Business processes and/or information systems get put into isolated silos.
• Confusion arises over data ownership and maintenance responsibility.
• Data definitions get mangled in translation from one system to another.
• Mergers and acquisitions occur, and company systems seem impossible to integrate.
• Quick and dirty ‘fixes’ are accomplished, but become permanent undocumented workarounds.

Business processes become hostage to the disintegration. They slow down. Errors increase, and groups dedicated to fixing them are formed. The situation comes to a point where executives that need to use the data to plan and make decisions don’t really trust it. “Personal data marts” start appearing and multiplying until there exists no single version of the truth. In the biblical story of the Tower of Babel, at least those building it realized that they were not able to communicate!

In this tutorial, participants will learn a proven, repeatable standard process for naming and describing their Enterprise data, no matter where the process is used in the organization.

Participants will learn:

• How the Tower of Babel gets built in the first place - why is it so easy to create this situation?
• How to hunt and gather the data that needs to be standardized in the organization
• Establish who is responsible for data descriptions and naming: it may need a partnership
• How to develop standard descriptions for data
• How to derive standard names from the description - describe first, then name!
• The best place to document the data once you have it defined
• How to sustain the effort

The participants will practice the standard techniques using examples that the instructor will provide in this interactive tutorial!