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Key benefits

Learn Delta’s core concepts and features as well as what makes it a perfect match for data engineering and analysis

Solve business challenges of different industry verticals using a scenario-based approach

Make optimal choices by understanding the various tradeoffs provided by Delta

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.

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.

What you will learn

Explore the key challenges of traditional data lakes

Appreciate the unique features of Delta that come out of the box

Address reliability, performance, and governance concerns using Delta

Analyze the open data format for an extensible and pluggable architecture

Handle multiple use cases to support BI, AI, streaming, and data discovery

Discover how common data and machine learning design patterns are executed on Delta

Build and deploy data and machine learning pipelines at scale using Delta

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Business Intelligence with Databricks SQL

€35.99

Simplifying Data Engineering and Analytics with Delta

€35.99

Data Engineering with Apache Spark, Delta Lake, and Lakehouse

€36.99

Total € 108.97

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Amazon verified reviews

Mukesh Aug 09, 2022

This is a very comprehensive book with all the details around data engineering’s and architecture. Great read, this will help a lot of individuals/ teams to deploy pipelines at scale.

Amazon Verified review

Arpita Singh Dec 07, 2022

This book is very well written for technical as well as non technical people interested in the world of data. I highly recommend everyone with a passion for data and digital transformation to read this book to educate and upskill themselves with up and coming trends in the data ecosystem.

vfortier Aug 10, 2022

Simplifying Data Engineering and Analytics with Delta not only covers why Delta helps in Data Engineering workloads but explain in details why and all the steps that are required to do proper data engineering no matter what tool you use. The first few chapters are great at explaining why Data Engineering is important to all data aspects (hint, it's to have data in the proper format at the proper time and in a cost effective manner).Starting with chapter 3 we dig into why Delta was required and the main features of delta and how it can be used to produce batch and streaming pipelines.I liked also the fact that this book included concise examples and full code to run all this.Section 12 will also be of interest to anyone that already has Delta in their data lake and want to optimize tables with all the tools available to do so in Delta.All in all great reference book to better learn data engineering in general and delta in specific.

Brian Flynn Sep 29, 2022

Given that the author is a veteran data practitioner, the value of their hands-on experience has rapidly accelerated my journey in learning and implementing the best open-source storage framework on the market. Whether you're a data practitioner with 2 years or 20 years of professional experience, this book is an essential addition to your collection.

Robert Reed Aug 01, 2022

The tech world thrives on change. Sorting out the hype from the value is the key to survival for businesses as societal change continues to accelerate.This particular book is a lucid and concise guide to understanding what "next" in the world of data storage and analysis at scale looks like - how to get business value out of all of your data whether structured or unstructured or both in combination.While not an in-depth treatise for training your data architects, it should appeal to all users looking to understand what a digital-first business should look like, today.

Simplifying Data Engineering and Analytics with Delta: Create analytics-ready data that fuels artificial intelligence and business intelligence

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