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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For the database world, the future looks extremely challenging—and, even more, exceedingly promising. Looking ahead over the next few years, organizations will be relying on their databases in ways never imagined, as leaders and decision makers look to their data resources for intelligence, real-time views, and adaptability to business changes.
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AI adoption is rapidly accelerating, but data quality and data governance remain two of the biggest challenges to successful implementation. While AI depends on vast amounts of data, the quality and accuracy of the information it processes directly determine its effectiveness. Strong data governance allows organizations to mitigate various threats, while poor data quality leads to inaccurate insights and inefficiencies.
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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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