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Available On-Demand - This webinar has been recorded and is now available for download.

Achieving Scalable, Agile, and Comprehensive Data Management and Data Governance: Research Insights from the Latest TDWI Best Practices Report (GMT Timezone)

Webinar Speaker: David Stodder, Senior Director of Research for BI, TDWI

Date: Wednesday, September 27, 2023

Time: 10:00 a.m. GMT

Data demands are exploding as organizations democratize access and expand into advanced analytics, artificial intelligence (AI), and machine learning (ML). Distributed data environments are putting stress on data integration, turning today’s labyrinth of pipelines and transformation processes into bottlenecks that affect downstream applications. Pressure is growing on legacy systems and practices, driving higher costs and reducing business value.

Data-driven business initiatives depend on scalable, agile, and comprehensive data management and data governance. Fortunately, AI/ML-infused innovation and automation are enabling organizations to modernize practices and take advantage of the latest in technology solutions such as cloud data platforms, data management tools, data catalogs, semantic layers, data virtualization, data fabrics, and data mesh.

Join this webinar to hear TDWI’s latest research regarding data management, data governance, and distributed data integration. TDWI will present findings from the new Best Practices Report about critical trends and drivers. We will report on organizations’ current experiences and future plans and will recommend best practices for solving challenges, particularly to accelerate growth in analytics and AI/ML.

Topics the webinar will cover include:

  • Addressing data governance challenges for protecting sensitive data and improving trust in quality
  • TDWI insights into data management trends and modernization priorities
  • Analytics and AI/ML: Using data management and governance for successful growth
  • How data integration is evolving to take advantage of modern technologies
  • Solving distributed data challenges with data mesh and data fabric architectures

David Stodder

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