While there are many courses and tutorials online, learning from a book is still one of the best ways to greatly improve your skills. Below I have selected top Big Data books.
- Big Data: A Revolution That Will Transform How We Live, Work, and Think (2014)
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems (2017)
- Big Data: Principles and best practices of scalable realtime data systems (2015)
- Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (2013)
- The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science (2019)
- Big Data For Dummies (2013)
- The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios (2017)
- Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are (2018)
- Storytelling with Data: A Data Visualization Guide for Business Professionals (2015)
- Big Data Science & Analytics: A Hands-On Approach (2016)
- Machine Learning: Beginner’s Guide to Machine Learning, Data Mining, Big Data, Artificial Intelligence and Neural Networks (2019)
- Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things (2017)
- Essentials of Statistics (5th Edition) (2014)
- Big Data Fundamentals: Concepts, Drivers & Techniques (The Prentice Hall Service Technology Series from Thomas Erl) (2016)
- Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)
“Illuminating and very timely . . . a fascinating — and sometimes alarming — survey of big data’s growing effect on just about everything: business, government, science and medicine, privacy, and even on the way we think.”—New York TimesIt seems like “big data” is in the news every day, as we read the latest examples of how powerful algorithms are teasing out the hidden connections between seemingly unrelated things.
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems (2017)
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application?
Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team.
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (2013)
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the “data-analytic thinking” necessary for extracting useful knowledge and business value from the data you collect.
The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises.
Big Data For Dummies (2013)
Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools.
The Big Book of Dashboards presents a comprehensive reference for those tasked with building or overseeing the development of business dashboards.
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are (2018)
Be prepared for next semester and get set for back to school!Foreword by Steven PinkerBlending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions.By the end of an average day in the Author(s): Seth Stephens-Davidowitz
Storytelling with Data: A Data Visualization Guide for Business Professionals (2015)
Don’t simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You’ll discover the power of storytelling and the way to make data a pivotal point in your story.
We are living in the dawn of what has been termed as the “Fourth Industrial Revolution”, which is marked through the emergence of “cyber-physical systems” where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT).
Machine Learning: Beginner’s Guide to Machine Learning, Data Mining, Big Data, Artificial Intelligence and Neural Networks (2019)
★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★If you’re looking for a way to become an expert Robot and impress your friends with the programs you can make from scratch, then keep readingArtificial Intelligence, and in particular, Machine Learning is here today and it is shaping our world. It is shaping and simplifying the way we live, work, travel and communicate.
Less than 0.5 per cent of all data is currently analysed and used. However, business leaders and managers cannot afford to be unconcerned or sceptical about data. Data is revolutionizing the way we work and it is the companies that view data as a strategic asset that will survive and thrive. Bernard Marr’s is a must-have guide to creating a robust data strategy.
You are purchasing a standalone product; MyStatLab does not come packaged with this content. If you would like to purchase both the physical text and MyStatLab, search for ISBN-10: 0133864960/ISBN-13: 9780133864960 That package includes ISBN-10: 0321847997/ISBN-13:9780321847997 ISBN-10: 032184839X/ISBN-13: andISBN-10: 0321924592 ISBN-13: 9780321924599 MyStatLab is not a self-paced technology and should only be purchased when required by an instructor.
Big Data Fundamentals: Concepts, Drivers & Techniques (The Prentice Hall Service Technology Series from Thomas Erl) (2016)
“This text should be required reading for everyone in contemporary business.” –Peter Woodhull, CEO, Modus21 “The one book that clearly describes and links Big Data concepts to business utility.” –Dr. Christopher Starr, PhD “Simply, this is the best Big Data book on the market!” –Sam Rostam, Cascadian IT Group “one of the most contemporary approaches I’ve seen to Big Data fundamentals” –Joshua M.
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017)
We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated.But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true.
Best Big Data Books Everyone Should Read
We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Library Genesis and download some big data books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.
Big Data Meets Survey Science: A Collection of Innovative Methods
Author(s): Craig A. Hill (editor), Paul P. Biemer (editor), Trent D. Buskirk (editor), Lilli Japec (editor), Antje Kirchner (editor), Stas Kolenikov (editor), Lars E. Lyberg (editor)
ID: 2669464, Publisher: Wiley, Year: 2021, Size: 8 Mb, Format: pdf
Multimedia Technologies in the Internet of Things Environment
Author(s): Raghvendra Kumar, Rohit Sharma, Prasant Kumar Pattnaik
ID: 2815334, Publisher: Springer Singapore, Year: 2021, Size: 8 Mb, Format: pdf
Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges
Author(s): Aboul Ella Hassanien, Ashraf Darwish
ID: 2850913, Publisher: Springer, Year: 2021, Size: 24 Mb, Format: pdf
Please note that this booklist is not errorless. Some books are really best-sellers according to Chicago Tribune, others are drafted by unknown authors. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant books you could recommend? Drop a comment if you have any feedback on the list.