Practical DataOps - Delivering Agile Data Science at Scale

Key Facts and Insights:

1. The importance of DataOps as a methodology for delivering Agile Data Science at scale.
2. The book proposes a model to implement DataOps in an organization.
3. An in-depth look at how to manage data as an asset.
4. Understanding the role of automation in the DataOps process.
5. Explanation of how to build an effective and efficient data pipeline.
6. A guide to measuring the success of DataOps using meaningful metrics.
7. Discussion of the technical, cultural and organizational challenges in implementing DataOps.
8. Insights into the role of AI and Machine Learning in DataOps.
9. Case studies of successful DataOps implementation...

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