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Explore how Delta brings reliability, performance, and governance to your data lake and all the AI and BI use cases built on top of it
Key Features:
Book Description:
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.
What You Will Learn:
Who this book is 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.
Author: Anindita Mahapatra
ISBN-10: 1801814864
ISBN-13: 9781801814867
Publisher: Packt Publishing
Language: English
Published: 07/29/2022
Pages: 334
Format: Paperback
Weight: 1.27lbs
Size: 9.25h x 7.50w x 0.70d
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