Simplifying Data Engineering and Analytics with Delta
This book is a practical guide for creating and executing data and ML pipelines using the open protocol Delta. Simplifying Data Engineering and Analytics with Delta focuses on helping you make the right architecture choices and providing a hands-on approach to implementation and associated methodologies that will have you up and running in no time.
Offered by
Difficulty Level
Intermediate
Completion Time
11h8m
Language
English
About Book
Who Is This Book For?
Data engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.
Simplifying Data Engineering and Analytics with Delta
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 11h8m total length
An Introduction to Data Engineering
Data Modeling and ETL
Delta – The Foundation Block for Big Data
Unifying Batch and Streaming with Delta
Data Consolidation in Delta Lake
Solving Common Data Pattern Scenarios with Delta
Delta for Data Warehouse Use Cases
Handling Atypical Data Scenarios with Delta
Delta for Reproducible Machine Learning Pipelines
Delta for Data Products and Services
Operationalizing Data and ML Pipelines
Optimizing Cost and Performance with Delta
Managing Your Data Journey
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