Enterprises often struggle with data silos, where information is scattered across disparate storage systems and teams, hindering collaboration and efficiency. This fragmentation results in duplicated data, increased costs, and delays in analytics and machine learning projects, as engineers spend valuable time locating and reshaping data. Addressing this requires a practical approach: first, create an inventory of existing data, then standardize on open protocols, and finally, build a unified access layer to connect these silos, prioritizing efforts based on business value.
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