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Unifying Analytics Across Warehouse, Lake and Into the Cloud

By: Gigaom

We’ve heard it before. A data warehouse is a place for formally-structured, highly-curated data, accommodating recurring business analyses, whereas data lakes are places for “raw” data, serving analytic workloads, experimental in nature. Since both conventional and experimental analysis is important in this data-driven era, we’re left with separate repositories, siloed data, and bifurcated skill sets.

Or are we? In fact, less structured data can go into your warehouse, and since today’s data warehouses can leverage the same distributed file systems and cloud storage layers that host data lakes, the warehouse/lake distinction’s very premise is rapidly diminishing. In reality, business drivers and business outcomes demand that we abandon the false dichotomy and unify our data, our governance, our analysis, and our technology teams.

Want to get this right? Then join us for a free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guest, David Dichmann from Cloudera. They’ll discuss how you can bring together the data warehouse, big data and AI, across the edge, the corporate data center and into the cloud.

In this 1-hour webinar, you will discover:

  • How it’s possible to do analytics on structured, unstructured, streaming, and machine data, all on an integrated platform
  • How data lake technology can compliment data warehouse platforms
  • How a unified approach gets your analytics into self-service/on-demand mode quickly

Register now to join GigaOm Research and Cloudera for this free expert webinar.

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Published:  Sep 16, 2019
Type:  Webinar