Learn about big data with these 7 books

Big data is everywhere and affects everyone from business owners to consumers to students to professionals in every field. We generate massive amounts of data every day just by going about our lives. In the right hands, data can help reveal insights, help solve problems, and help change the world for the better. But in uninformed hands, data can be misinterpreted and misused. This selection of books covers everything from business advice to cautionary tales, showing the many ways big data can affect us all for better and worse.

1. “Big Data: A Revolution That Will Transform How We Live, Work, and Think” by Viktor Mayer-Schönberger and Kenneth Cukier

Authors: Viktor Mayer-Schönberger and Kenneth Cukier Website: Amazon Big data is already changing the world and it’s about to get bigger. In this book, authors Mayer-Schönberger and Cukier explain what effect big data has at finding patterns and simplifying tasks. They also explain the issues with big data in just about every aspect of our lives. Big data isn’t just in businesses or technology, it also exists in our education, healthcare, and government. The more data we collect, the more information we have on people as a whole. As we use more data in more automation, we also have to consider the cost of privacy versus the growing ease and efficiency of data-driven work.

2. “Too Big to Ignore: The Business Case for Big Data” by Phil Simon

Authors: Phil Simon Website: PhilSimon.com | Amazon How do product recommendations work? How do ads target customers? Automated systems like these are an increasingly prolific trend in big data. Not only have we never had access to so much information, we’ve also never used so much. And we may have only scratched the surface of innovative uses of data. In this book, Phil Simon explains the benefits of big data in a business sense and how to use it to your advantage. This book is for business professionals looking to use big data to reach their targets. It explains how organizations make use of the extreme volume of data, sifting through it to find the relevant patterns in order to make decisions or predictions. Simon uses case studies, examples, and quotes from industry leaders to show how valuable big data is in today’s business world.

3. “Big Data at Work: Dispelling the Myths, Uncovering the Opportunities” by Thomas H. Davenport

Authors: Thomas H. Davenport Website: Amazon In “Big Data at Work,” Davenport tackles the concept of big data and what it really means for businesses. Meant for managers who want to start incorporating big data into their business, the book is a good introduction, using clear and simple terms. The book details what technologies are needed to take advantage of big data, as well as how to go about incorporating it. Davenport draws from examples to show how businesses have succeeded and failed using big data practices. Company examples such as Amazon, UPS, and Citigroup are shown to highlight the opportunities for big data at hand.

4. “Big Data For Dummies” by Judith Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman

Authors: Judith Hurwitz, Alan Nugent, Fern Halper, and Marcia Kaufman Website: Amazon “Big Data For Dummies” is an introduction to the world of big data for anyone who has no prior experience but wants to get started. In this book, the authors explain how to manage big data, store it, analyze it, and find solutions from the noise. Many traditional data tools are incapable of handling the enormous amounts of data generated every day, which leaves businesses wanting. The book details technologies available for big data and how the cloud is involved. Also covered are some finer points, like: how to secure data, how to manage it, and how to implement solutions.

5. “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy” by Cathy O’Neil

Authors: Cathy O’Neil Website: Site | Amazon While big data is essential for businesses to capitalize on or for researchers to study the public, it also raises alarm bells for personal privacy. How much of the data we generate is data we own? Not much. And how many business intelligence decisions take into account a holistic view of cultural impact? Not many. O’Neil discusses the downsides of an automated world, where technology is mostly unregulated and can incentivize data-driven decisions that secretly encourage disparity and inequality. With real-world examples, she shows how algorithms and models can inadvertently cause long-term and systemic damage. Business—and even policy—decisions are being made more often with the help of algorithms. O’Neil implores readers to question the status quo and become more knowledgeable about the algorithms present in our lives.

6. “Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are” by Seth Stephens-Davidowitz

Authors: Seth Stephens-Davidowitz Website: Site | Amazon Humans generate incomprehensible amounts of data every day without even knowing it. The websites we visit, the searches we Google, the places we go, the food we buy—everything that can be a data point is a data point. We are creating massive amounts of data with everything we do. Every action we make notes something about ourselves, a practice was practically unknown in the analog past. After all, nearly everyone runs around with smartphones packed with apps taking in information about our every move and action. “Everybody Lies” takes a look at all the data we unconsciously generate and what it reveals about ourselves. There are narratives and trends buried within information about demographics, voter preferences, education potential and success, and even how often we lie about our lives.

7. “Numbersense: How to Use Big Data to Your Advantage” by Kaiser Fung

Authors: Kaiser Fung Website: Site | Amazon “Numbersense” is a little different from most of these other books. Rather than teaching readers about what big data is or how to harness the power of data for their business, it instead offers a critical look at interpreting analysis and critiquing results. While more data often gives us better insights, we still need to filter out the right noise to get to the insights in the information. It also means that the more data we have, the more we have to filter out, and the harder it is to interpret. “Numbersense” questions widely accepted information, such as whether we can trust unemployment data issued by governments or whether the college ranking systems are even close to accurate indicators of performance. It instructs readers not to take data for granted and to understand the methods that lead to interpretation. With a wealth of data at our fingertips, sometimes bad information can leak through. It’s up to us to question and verify. When you understand how the analysis works, then you can make better decisions. Disclaimer: Tableau does not officially endorse nor profit from any products, or opinions therein, listed in this article and as such this page does not engage with any affiliate link programs. This article is intended purely for educational purposes and the above information about products and publications is made available so that readers can make informed decisions for themselves.