Data has taken a new position in the spotlight as the most important part of using AI. If the organization is using corrupt data, insights will vary wildly, and misinformation can damage the company's reputation. Poor data quality costs organizations at least $12.9 million per year on average, according to Gartner research from 2020.
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The Call for Speakers is officially open for the 13th annual Data Summit, taking place in Boston on May 6-7, 2026, with pre-conference workshops on May 5. The deadline to submit proposals is December 12, 2025.
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In recent months, the ground has been moving underneath the feet of the overseers of enterprise data and IT environments. AI is bringing new challenges, along with seemingly insatiable business demands for real-time insights. To explore the most compelling technologies promising to shape the data world in the months and years to come, we canvassed market leaders to get a sense of the top technological changes and potential issues that may arise.
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Application modernization is the strategic process of updating legacy software to leverage modern technologies and methodologies, transforming older systems into flexible, cloud-native solutions. This shift allows businesses to move faster, improve performance, and integrate cutting-edge tools like AI.
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