The amount of data and its complexity has been growing at a rapid clip and shows no sign of stopping. To contain this data, organizations have been introducing different types of database platforms alongside relational solutions. To help organizations progress along their data-driven journeys, each year, DBTA presents the Readers' Choice Awards, which provide the opportunity to recognize companies whose products have been selected by the experts—our readers!
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Organizations consistently struggle to manage what are known as "long-tail" data connectors. These are connectors that are less used and not available on many legacy data integration platforms. As a result, often organizations have had to build their own custom pipelines and, worse yet, maintain and rebuild those as data sources changed over time as requirements evolved.
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If you've worked in any data-centric role, you've probably experienced the effects of the proverbial "mandate from on high." Someone in the C-suite decides it's time to hop on the latest shift in the tech landscape—whether generative AI, hybrid cloud infrastructure, or remote work—and now it's time for the entire tech department to make it happen.
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With the rapid success of OpenAI's ChatGPT and other emerging types of AI solutions in the last several years, organizations have been scrambling to adopt artificial intelligence by "any means necessary." This pivot has changed how organizations think about modern enterprise data architecture.
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