Learning about how to use the latest data compression in your operations doesn’t have to be a mystery. We’ve curated the top books to help you understand information theory and modern compression for technical operations in 2019 and beyond.

Introduction to Information Theory and Data Compression (Applied Mathematics) 2nd Edition – Peter D. Johnson Jr. (Author), Greg A. Harris (Author), D.C. Hankerson (Author)

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An effective blend of carefully explained theory and practical applications, this text imparts the fundamentals of both information theory and data compression. Although the two topics are related, this unique text allows either topic to be presented independently, and it was specifically designed so that the data compression section requires no prior knowledge of information theory.

Understanding Compression: Data Compression for Modern Developers 1st Edition
– Colt McAnlis (Author), Aleks Haecky (Author)

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If you want to attract and retain users in the booming mobile services market, you need a quick-loading app that won’t churn through their data plans. The key is to compress multimedia and other data into smaller files, but finding the right method is tricky. This witty book helps you understand how data compression algorithms work—in theory and practice—so you can choose the best solution among all the available compression tools.

With tables, diagrams, games, and as little math as possible, authors Colt McAnlis and Aleks Haecky neatly explain the fundamentals. Learn how compressed files are better, cheaper, and faster to distribute and consume, and how they’ll give you a competitive edge.

Introduction to Data Compression (Morgan Kaufmann Series in Multimedia Information and Systems) – Khalid Sayood (1996-01-04) Hardcover – 1846

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Notes from Reviewers:

This is one of those books that only gets a new edition when the author has something genuinely new to say, and this third edition of Sayood’s excellent introduction to data compression is no exception. This particular edition is different from the second mainly in that there is a new chapter on audio compression that includes a description of the mp3 algorithm. Also there is additional information on the new video coding standards as well as the new facsimile standards.

As to the target audience for this book, if you are tasked with designing hardware or software implementations of data compression algorithms and you have some background in either electrical engineering or computer science, then this is a good book from which to learn and then to practice what you learn via some very good exercises. Some prior knowledge of information theory and random processes wouldn’t hurt either. There is also an abundance of examples that are sprinkled throughout the book to illustrate concepts as they are presented. The author’s approach in each chapter is to explain each concept in as an accessible manor as possible, present relevant equations, and then work an example using what has just been presented.