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Simplifying Data Engineering and Analytics with Delta
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Simplifying Data Engineering and Analytics with Delta
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Overview of this book
Delta helps you generate reliable insights at scale and simplifies architecture around data pipelines, allowing you to focus primarily on refining the use cases being worked on. This is especially important when you consider that existing architecture is frequently reused for new use cases.
In this book, you’ll learn about the principles of distributed computing, data modeling techniques, and big data design patterns and templates that help solve end-to-end data flow problems for common scenarios and are reusable across use cases and industry verticals. You’ll also learn how to recover from errors and the best practices around handling structured, semi-structured, and unstructured data using Delta. After that, you’ll get to grips with features such as ACID transactions on big data, disciplined schema evolution, time travel to help rewind a dataset to a different time or version, and unified batch and streaming capabilities that will help you build agile and robust data products.
By the end of this Delta book, you’ll be able to use Delta as the foundational block for creating analytics-ready data that fuels all AI/BI use cases.
Table of Contents (18 chapters)
Preface
Section 1 – Introduction to Delta Lake and Data Engineering Principles
Free Chapter
Chapter 1: Introduction to Data Engineering
Chapter 2: Data Modeling and ETL
Chapter 3: Delta – The Foundation Block for Big Data
Section 2 – End-to-End Process of Building Delta Pipelines
Chapter 4: Unifying Batch and Streaming with Delta
Chapter 5: Data Consolidation in Delta Lake
Chapter 6: Solving Common Data Pattern Scenarios with Delta
Chapter 7: Delta for Data Warehouse Use Cases
Chapter 8: Handling Atypical Data Scenarios with Delta
Chapter 9: Delta for Reproducible Machine Learning Pipelines
Chapter 10: Delta for Data Products and Services
Section 3 – Operationalizing and Productionalizing Delta Pipelines
Chapter 11: Operationalizing Data and ML Pipelines
Chapter 12: Optimizing Cost and Performance with Delta
Chapter 13: Managing Your Data Journey
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