Section 3 – Operationalizing and Productionalizing Delta Pipelines

A lot of ML projects fail to see the light of production. Beyond a POC, there are several considerations to take a pipeline to production and ensure it is resilient and runs 24*7, adapting to changes in data patterns and business needs to continuously provide value. Cost and performance are important considerations as data scales. Automation is mandatory to continuously refine and evolve a pipeline. ML models once unleashed are living assets and their life cycle management is yet another layer of the underlying data pipeline that needs to be monitored and managed to ensure they produce the expected ROI for the business.

This section includes the following chapters:

• Chapter 11, Operationalizing Data and ML Pipelines
• Chapter 12, Optimizing Cost and Performance with Delta
• Chapter 13, Managing Your Data Journey