Data pipelines require an extensive amount of tooling in order to support efficient data usage. The following covers what it means to actually get data into an environment in a prepared way so data scientists can begin their analyses.
Key learning objectives:
Understand the difference between open source and proprietary
Define the importance of the data pipeline and its individual components
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