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Part 1 £¿ Introduction to Data Engineering, Scala, and an Environment Setup
Chapter 1: Scala Essentials for Data Engineers
Chapter 2: Environment Setup
Part 2 £¿ Data Ingestion, Transformation, Cleansing, and Profiling Using Scala and Spark
Chapter 3: An Introduction to Apache Spark and Its APIs £¿ DataFrame, Dataset, and Spark SQL
Chapter 4: Working with Databases
Chapter 5: Object Stores and Data Lakes
Chapter 6: Understanding Data Transformation
Chapter 7: Data Profiling and Data Quality
Part 3 £¿ Software Engineering Best Practices for Data Engineering in Scala
Chapter 8: Test-Driven Development, Code Health, and Maintainability
Chapter 9: CI/CD with GitHub
Part 4 £¿ Productionalizing Data Engineering Pipelines £¿ Orchestration and Tuning
Chapter 10: Data Pipeline Orchestration
Chapter 11: Performance Tuning
Part 5 £¿ End-to-End Data Pipelines
Chapter 12: Building Batch Pipelines Using Spark and Scala
Chapter 13: Building Streaming Pipelines Using Spark and Scala
Index
Other Books You May Enjoy |
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Tome, Eric
Eric Tome has over 25 years of experience working with data. He has contributed to and led teams that ingested, cleansed, standardized, and prepared data used by business intelligence, data science, and operations teams. He has a background in mathematics and currently works as a senior solutions architect at Databricks, helping customers solve their data and AI challenges.
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