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Fern Halper, Ph.D.

VP and Research Director for Advanced Analytics

James Kobielus

Senior Research Director for Data Management

For years, TDWI research has tracked the modernization and evolution of data warehouse architectures, as well as the emergence of the data lake design pattern for organizing massive volumes of analytics data. The two have recently converged to form a new and richer data architecture. The architecture is fairly new, and not many organizations have embraced it yet, although the majority of respondents to our recent TDWI Best Practices Report survey see it as an opportunity because it provides more options for managing an increasingly diverse range of data structures, end user types, and business use cases.

Within this evolved environment, data warehouses and data lakes can incorporate distinct, but integrated, overlapping, and interoperable architectures that incorporate standard functional layers. These unifying layers include data storage, mixed workload management, data virtualization, content ETL, and data governance and protection. This unified DW/DL architecture continues to evolve, blurring the architectural distinctions between these formerly discrete approaches to deploying, processing, and managing analytics data.

Join TDWI Research VP Fern Halper and TDWI Senior Research Director James Kobielus as they discusses the results of their most recent Best Practices Report on building the unified data warehouse and data lake.

Topics will include:

  • An introduction to the unified DW/DL including use cases and business value
  • How organizations are accomplishing unification
  • Data pipelines supporting unification
  • Organizational considerations for the unified DW/DL
  • Best practices for moving forward

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