RESEARCH & RESOURCES

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

Modernizing Data Integration to Accommodate New Big Data and New Business Requirements

TDWI Speaker: Philip Russom, TDWI Research Director

Date: Wednesday, December 16, 2015

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

Webinar Abstract

There’s a lot of buzz currently about how many types of IT systems need updates, upgrades, extensions, and replacements, due to recent changes in business and technology requirements. Current parlance refers to these collectively as “modernization” projects.

Like most enterprise software solutions, data integration (DI) needs modernization in many organizations, too. Some organizations will adopt new practices and tools, for early ingestion, schema on read, light data prep, and ELT pushdown into new platforms like Hadoop. For others, modernization is more about methodologies and development practices, such agile and lean DI. Some organizations still haven’t started using established DI functions for federation, virtualization, in-memory processing, and real-time operation; so, for them, modernization is about getting caught up. Although a lot of new functions and methods are coming into DI, they won’t replace the old ones, so you have to know and practice both.

These and related advancements are addressed in a new Checklist Report by TDWI’s Philip Russom called “Modernizing Data Integration to Accommodate New Big Data and New Business Requirements.” That report was sponsored by vendor firm SAS, and the content of this Webinar is based on the research findings of that report. People who register to attend the Webinar can receive a copy of the recently published TDWI Checklist Report on Data Integration Modernization.

What the audience will learn:

  • Trends that are driving the need for data integration modernization
  • Modernization strategies that users are taking
  • New data platforms and tools that users are applying in their DI modernization projects, as well as new skills and team structures
  • The future of modern data integration

Philip Russom, Ph.D.

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