Most data management professionals understand the negative impact of poor or no data architecture practices. Often, the design is completed up front and the model becomes a nice piece of art hanging on the wall with no practical value. Or, there is little or no upfront design and it becomes the Wild West. This leads to confusion, misinterpretation or unnecessary creative liberties, ultimately wasting time and effort and directly impacting the bottom line.
It’s also true that most data management professionals understand the value of data modeling and architecture. Upfront design can reveal design flaws early in the process, enabling them to be corrected during the design or development phase, rather than waiting until post-production when the cost involved skyrockets. What’s more, a blueprint of the data provides traceability for strategic initiatives like master data management, business intelligence, data governance and data warehousing while also providing impact analysis so that changes are implemented into the system faster and easier. Shared and consistent definitions provide a holistic view of the data across systems, so reuse, rather than reinvention, is promoted.
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