[Databricks] The Big Book of Data Engineering 2nd Edition

big-book-of-data-engineering-2nd-edition-final.pdf

8.85MB

 

 

 

1. Introduction to Data Engineering on Databricks

2. Guidance and Best Practices

2.1. The 5 Databricks Performance Tips

2.2. How to Profile PySpark

2.3. Low-Latency Streaming Data Pipelines With Delta Live Tables and Apache Kafka

2.4. Streaming in Production: Collected Best Practices

2.5. Streaming in Production: Collected Best Practices, Part 2 

2.6. Building Geospatial Data Products

2.7. Data Lineage With Unity Catalog

2.8. Easy Ingestion to Lakehouse With COPY INTO

2.9. Simplifying Change Data Capture WIth Databricks Delta Live Tables.

2.10. Best Practices for Cross-Government Data Sharing

 

3. Ready-to-Use Notebooks and Data Sets

 

4. Case Studies

4.1. Akamai 

4.2. Grammarly 

4.3. Honeywell

4.4. Wood Mackenzie

4.5. Rivian

4.6. AT&T