Bringing Data Warehouse and Data Lake Capabilities Together

This free 1-hour webinar from GigaOm Research brings together experts in data warehouse, featuring GigaOm analyst Andrew Brust.

A modern analytics stack is needed to take on the Internet of Things (IoT), build predictive models, and perform statistical, time series & geospatial analysis. In short, digital transformation relies on an enlightened approach to data analytics. Can data warehouse platforms satisfy these requirements?

In this free 1-hour webinar, GigaOm Research Analyst Andrew Brust covers:

  •  How the machine learning and analytics stacks can be integrated
  • Why sub-clustering changes the data warehouse equation
  • What workload management and enhanced SQL capabilities are, and how they tie in

Why Attend

Leaving data in raw form; performing analysis with different query and programming languages; and building machine learning models are a few of the many reasons companies have found the data lake model appealing. Spinning up task-specific compute clusters and having them share data is another. But data lakes no longer offer the exclusive route to these capabilities.

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