| #2 |  Fundamentals of Data Engineering Fundamentals of Data Engineering: Plan and Build Robust Data Systems
| 4 | 7 reads | |
| #3 |  Learning Spark: Lightning-Fast Big Data Analysis
| 2 | 2 reads | |
| #4 |  Hadoop Hadoop: The Definitive Guide
| 3 | 1 read | |
| #5 |  Data Pipelines with Apache Airflow
| 0 | 1 read | |
| #6 |  Data Pipelines Pocket Reference: Moving and Processing Data for Analytics
| 3.8 | 5 reads | |
| #7 |  Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
| 4.66 | 76 reads | |
| #8 |  Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
| 3 | 2 reads | |
| #9 |  The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling
| 4.67 | 4 reads | |
| #10 |  Snowflake: The Definitive Guide: Architecting, Designing, and Deploying on the Snowflake Data Cloud
| 0 | 0 reads | |
| #11 |  SQL Pocket Guide: A Guide to SQL Usage by Jonathan Gennick, O'Reilly Media
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| #12 |  Data Mesh: Delivering Data-Driven Value at Scale
| 3 | 1 read | |
| #13 |  Building Analytics Teams Building Analytics Teams: Harnessing analytics and artificial intelligence for business improvement
| 4 | 1 read | |
| #14 |  Data Teams Data Teams
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| #15 |  DAMA-DMBOK: Data Management Body of Knowledge
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