![]() That, however, meant degrading a lot of the data because it wasn’t all meant to fit together. ![]() To get business intelligence, it would be necessary to take all the data and put it in a central place a data warehouse or data lake. However, everything was built strictly for running the business, so analytics were secondary. Then came the realization that insights could be derived from all that data. That meant identifying your operational systems, the data in them, then capturing and storing that data in built-for-use databases focused on processes and operations. Usually to capture, move and manage customers through a business process. Traditionally, data architectures were designed to support the day-to-day operations of a business. However, implementing a modern data architecture that effectively serves businesses can be a distinct challenge. ![]() As organizations continue to view their data as an asset over simply a necessary cost to do business, the focus on structuring data for its best use increasingly becomes a top priority. Modernizing data architectures is a crucial endeavor for organizations to stay competitive and make better use of their data assets. ![]()
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