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While data lakes are booming in popularity thanks to their usefulness in storing large amounts of unstructured data sets and their ease in collecting raw data for analysis, businesses often find themselves building extensive data architectures consisting of extracts, cubes, and ETL so they can organize and use the data in them.
However, the flexibility, scalability, and cost-effectiveness of data lakes doesn’t have to come at the expense of query speeds and utility.
Read this white paper to learn how to use a powerful data lake engine like Dremio’s and skip the expensive infrastructure.
- Vendor:
- Dremio
- Posted:
- Feb 8, 2021
- Published:
- Jul 27, 2020
- Format:
- Type:
- White Paper
