EP7 - Getting Started with Hadoop Migration and Modernization
Most companies use Hadoop for big data analytical workloads. The problem is, on-premises Hadoop deployments have failed to deliver business value after it is implemented. Over time, the high cost of operations and poor performance places a limitation on an organization’s ability to be agile. As a result, data platform teams are looking to modernize their Hadoop workloads to the data lakehouse.
In this video, you'll learn about:
Use cases for modernizing Hadoop workloads
How the data lakehouse solves the inefficiencies of on-premises Hadoop
Success stories from organizations that have modernized Hadoop with the data lakehouse on Dremio
Below are additional resources that I thought you might find helpful:
Slide Deck.
Q&A.
Apache Iceberg - An Architectural Look Under The Covers. https://www.dremio.com/resources/guid...
The Path to Self-Service Analytics on the Data Lake. https://hello.dremio.com/wp-the-path-...
Getting Started with Hadoop Migration and Modernization. https://hello.dremio.com/webcast-gett...
See all upcoming episodes: https://www.dremio.com/gnarly-data-wa...
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