The sun is setting on the “old ways” of managing data at modern financial institutions. Spurred on by new regulation, intense competition, and the scale of modern data challenge — mapping and managing information principally based on rules is on the way out. In its place, the largest financial organizations are turning to machine learning to more precisely manage their complex and diverse data ecosystems.
Daniel Waldner, Principal Strategist at Traction on Demand and Alex Batchelor, Strategic Sales Engineer at Tamr recently sat down with Mike Meriton, Moderator, Co-Founder & COO, EDM Council to discuss how industry experts are driving this change today.
- The "tried, tested, and true" rules-based approach to data mastery cannot continue to work effectively with the modern growth of data.
- Leveraging machine learning and artificial intelligence to handle mastery is the only way to master data with large growth.
- Machine learning mastery isn't just theory; it's already implemented in a number of big organizations, and the power is proven.
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Why Finance is turning to machine learning to manage data
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Are you still applying the “old ways” of managing data — mapping and managing information principally based on rules? Today, the largest financial organizations are turning to machine learning to more precisely manage their complex and diverse data ecosystems. If you're interested in implementing industry-leading data systems of your own, our team at Traction on Demand can help get you there.