Practical Considerations for Building a Data Lake
Building an operational data lake has proven to be harder than most people thought. There are many technical challenges you have to take care of that are not handled out of the box by Hadoop, Spark, serverless platforms, or any of the new data architecture technologies. In addition, as many organizations are moving to the cloud, there are emerging challenges of multi-cloud and multi-big data platform management that many organizations are just starting to deal with.
Matt Aslett of 451 Research discusses these issues, along with approaches you should consider in overcoming them. He will also address the importance of automation in dealing with challenges around:
- Data ingestion and data prep
- High performance data access
- Data governance
- Building and running data pipelines
- Cross-platform (cloud and on premise) data management
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