What would be considered data management best practices?

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What would be considered data management best practices?


Adrienne Tannenbaum’s Answer: Best practices in data management are entirely dependent on the organization. For example, organizations that are focused primarily on the purchase of packaged solutions would have different objectives with regard to data management as compared to very large organizations with a substantial amount of custom developed applications, both legacy and newly integrated.

For the most part, data management’s objective is to standardize and reuse accurate data, focusing on the set of data that is clearly "corporate" in that it does not change across departments and applications. Examples of such data are "customer data" (customer ID, customer name, etc.), "employee data" (employee name, SS number, job title, etc.), "product data" and so on.

Data management is something that should be established from the beginning. Unfortunately most organizations wait until data is out of hand. This is often realized once a data warehouse or data mart is built and the data that is loaded just doesn’t compare to existing production reports. These organizations then try to retrofit a new "data management philosophy" into a world of departments that has been working with their own information on their own terms. This is not always successful.

"Best practices" are those that cannot be bypassed and do not cause aggravation to the creators and ultimate users of the data. Think about how easy it would be for people to search for customer data and instantly find the data that is correct, valuable and maintained. Best practices would aspire to this. Organizations that fail typically try to do too much at once with limited resources. We always recommend focusing on the data management aspect that gives you the biggest bank for your buck. This must include the creation and maintenance of "active meta data" along with the creation and maintenance of the data itself. Six months should be the longest amount of time that it takes to see a beneficial impact of a roll-out practice.

Sid Adelman’s Answer: That’s a very broad question. You may want to look at DCI’s eUniversity, at www.crmcommunity.com. They have a Web-based data strategy class (it’s actually my class) that addresses some of the data management best practices. I’m co-authoring a book with Larissa Moss and Majid Abai entitled Data Strategy that will cover most data management best practices. The book should be on the shelves in the second half of 2004.

Clay Rehm’s Answer: There are far too many practices to list in this space. There are books available that identify data management best practices. Search on the Internet for data management and data management best practices.

Data management must have a methodology that you follow. This must be documented, easy to find and easy to use. There should not be exceptions to using it – it must be flexible enough to be modified for almost every situation.

Other best practices include:

  • Data stewardship and ownership
  • Enforcement of data quality
  • Integration of data across enterprise
  • Naming standards and consistency
  • Required use of data models
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