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The Data Architect

For data architects, it can seem like one step forward and two steps back

As enterprise applications continue to evolve and their data requirements change, keeping tabs on the enterprise's data assets and avoiding costly replicated efforts and errors becomes a challenging task. Applications would benefit by leveraging existing data assets, where possible - applying integration technologies to get a coherent picture of enterprise data. While there are several methods available for integrating data assets, many situations are too complex or require more flexibility than some traditional options allow.

Enterprises spend significant resources keeping their data architectures manageable and useful for the people who need the assets they contain. For data architects, it can seem like one step forward and two steps back - spend significant effort keeping track of OLTP systems, data warehouses and data marts; building metadata repositories; and developing, and sometimes even reverse engineering data models, only to see the rise of more stovepipe databases and applications.

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