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

What’s Ahead in Data Management in 2020?

Webinar Speaker: Philip Russom, Senior Research Director for Data Management

Date: Wednesday, December 18, 2019

Time: 9:00 a.m. PT, 12:00 p.m. ET

According to Bob Dylan: “The times they are a-changin’.” In the field of data management today, this means a number of exciting but challenging developments:

Data itself is evolving into larger volumes, from new sources, in a broadening array of structures, containers, interfaces, and latencies. New data-driven business use cases are rising in prominence, especially those for analytics, self-service, and agile operations. In response to user demands, the software vendor and open source communities are supplying many new data platforms, tools, and capabilities—all purpose-built for modern data and its use cases.

This webinar is a “must attend” for technical users and business managers who are facing these changes. The expert panel on this webinar will help attendees understand what’s ahead in 2020 and beyond for data management. Attendees can then apply that information to prioritize the data management changes they must address, plus how they will prepare via hiring, training, budgeting, making a business case, and adopting just the right data platforms and tools.

The webinar brings together a panel of experts, moderated by Philip Russom, TDWI’s lead analyst for data management. The panel will discuss the hotter trends in data management, including:

  • Evolving data volumes, structures, sources, interfaces, and latencies
  • New data platforms, such as Hadoop, clouds, object storage, and databases based on columns, NoSQL, graph, etc.
  • Cloud for data management, including data warehousing, integration, and analytics
  • Advancements in catalogs, glossaries, metadata, and other data semantics
  • Automation for development productivity and production optimization
  • The rise of machine learning and artificial intelligence, plus how data management must provision the right data for success with predictive analytics

Philip Russom, Ph.D.

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