18 Best Books on Big Data

Best Books on Big Data

Never before in the history of the world have we gathered as much information that we do today. As we continue to move forward in the information age, everything appears to be digitalized, tracked, and analyzed. Mountains of big data are stored, analyzed, and produced. Traditional IT systems can’t keep up with the massive amounts of data sets that are being produced. Today, engineers are building new systems that we may store, process, and acquire bid data in this on-going stream of big data. It is to no surprise that big data has and will continue to transform our lives, our work, and even how we think. That’s why this list of the best books on big data can give you a well-rounded understanding of big data.

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What is Big Data and How is it Created?
Best Books on Big Data: THE LIST
Final Thoughts

What is Big Data and How is it Created?

In short, big data refers to a wide range of diverse sets of data that is massively complex and are rapidly increased in the velocity of speed, in which, the volume of the data is collected, analyzed, and created. Big data is categorized into structured or unstructured and organized into databases or spreadsheets, normally in numeric values.

Best Books on Big Data: THE LIST

1.  Confident Data Skills
2.  Astroball
3.  Reinventing Capitalism in the Age of Big Data
4.  What to do When Machines Do Everything
5.  User Research
6. Data-Driven
7. Predictive Analytics
8. The Data-Driven Leader
9. Big Data in Practice
10. Mind + Machine
11. Data-ism
12. What Stays in Vegas
13. Big Data
14. Taming the Big Data Tidal Wave
15. Search
16. Behind Every Good Decision
17. The Naked Future
18. Think Bigger
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1 – Confident Data Skills | Kirill Eremenko and Kogan Page

Data has dramatically changed how our world works. Understanding and using data is now one of the most transferable and desirable skills. Whether you’re an entrepreneur wanting to boost your business, a job seeker looking for that employable edge, or simply hoping to make the most of your current career, Confident Data Skills is here to help.

This updated second edition takes you through the basics of data: from data mining and preparing and analyzing your data, to visualizing and communicating your insights. It now contains exciting new content on neural networks and deep learning. Featuring in-depth international case studies from companies including Amazon, LinkedIn, and Mike’s Hard Lemonade Co, as well as easy-to-understand language and inspiring advice and guidance, Confident Data Skills will help you use your new-found data skills to give your career that cutting-edge boost.

Quotes from Confident Data Skills;

“Understanding not only what the problem is but also why it must be resolved now, who its key stakeholders are, and what it will mean for the institution…will help you to start refining your investigation.”

“If the raw data is not first structured properly in the data set, then the later stages of the process will either not work at all or, even worse, will give…inaccurate predictions and/or incorrect results.”

Data preparation is always going to be time-consuming, but the more due diligence you take in this stage, the more you will speed up the Data Science Process as a whole.”

“To create advocates: Don’t guard your secrets like a jealous magician. Go out of your way to show your clients the approach you have taken and how data science can vastly improve their business.” 

“In an age where so many jobs are at risk of being made obsolete within 20 years, data science should be an area of interest for anyone looking for job security, let alone an interesting career path.”

2 – Astroball | Ben Reiter

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When Sports Illustrated declared on the cover of a June 2014 issue that the Houston Astros would win the World Series in 2017, people thought Ben Reiter, the article’s author, was crazy. The Astros were the worst baseball team in half a century. The cover story, combined with the specificity of Reiter’s claim, met instant and nearly universal derision. But three years later, the Astros won the World Series for the first time in their history. How had Reiter predicted it so accurately? And, more importantly, how had the Astros pulled off the impossible? Astroball is the inside story of how a gang of outsiders went beyond Moneyball s data revolution to find a new way to win. They did so by combining hard data with the human judgment of the scouts who had been marginalized by the modernization of their sport. The lessons they learned stretch far beyond baseball into big business and other professional sports. Astroball is a ground-breaking look at the cutting edge of evaluating and optimizing human potential.

Quotes from Astroball;

“Whether you sell insurance or you’re a school teacher, obviously the people you work with can make you more productive or less productive,”

“Innovation, by definition, suggests change will be taking place,” Sig said. “If there’s a change taking place, it’s not likely going to feel right. If it felt right, it would have been done a long time ago.”

“In 2013, one of the Cardinals’ rival scouting departments commissioned a study that examined draft outcomes more deeply still. The study, which extended back to 1990, found that if a club’s draft produces nine players who appear in the majors for even a single game, it ranks in the 95th percentile. The 95th percentile for number of everyday players—defined as those who go on to accumulate 1,500 big league plate appearances or batters faced—is four. The 95th percentile for number of firmly above-average players—that is, those who produce a cumulative Wins Above Replacement above 6.0 in their six cost-controlled, pre–free agency seasons—is three.”

3 – Reinventing Capitalism in the Age of Big Data | Vikto Mayer-Schonberger, and Thomas Ramge

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From the New York Times bestselling author of Big Data, a prediction for how data will revolutionize the market economy and make cash, banks, and big companies obsolete. In modern history, the story of capitalism has been a story of firms and financiers. That’s all going to change thanks to the Big Data revolution. As Viktor Mayer-Schörger, bestselling author of Big Data, and Thomas Ramge, who writes for The Economist, show, data is replacing money as the driver of market behavior. Big finance and big companies will be replaced by small groups and individual actors who make markets instead of making things: think Uber instead of Ford, or Airbnb instead of Hyatt. This is the dawn of the era of data capitalism. Will it be an age of prosperity or of calamity? This book provides the indispensable roadmap for securing a better future.

Quotes from Reinventing Capitalsim in the Age of Big Data;

The future of our economy lies in the clever exploitation of our informational surplus, and data-rich markets are the mechanisms and the places where we can achieve this.”

“Like other markets, data-driven ones require rules (and their stringent enforcement) to make sure that decision making remains decentralized and markets remain efficient.”

“Data-driven markets offer such compelling advantages over traditional, money-based ones that their advent is assured.”

“We argue that a reboot of the market fueled by data will lead to a fundamental reconfiguration of our economy, one that will be arguably as momentous as the Industrial Revolution, reinventing capitalism as we know it.”

“Services based on machine learning systems fueled by feedback data ‘buy’ innovation at diminishing cost as the user base grows. It feels strangely alchemistic: turning a by-product of usage into the raw material of improvement, like converting lead into gold.”

4 – What To Do When Machines Do Everything | Malcolm Frank, Paul Roehrig, and Ben Pring

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What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created.

Written by a team of business and technology expert practitioners―who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business―this book provides a clear path to the future of your work.

The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives―Automate, Halos, Enhance, Abundance, and Discovery―that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy, and innovation.

Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you;

  • Understand the untold full extent of technology’s impact on the way we work and live.
  • Find out where we’re headed, and how soon the future will arrive
  • Leverage the new emerging paradigm into a sustainable business advantage
  • Adopt a strategic model for winning in the new economy

The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don’t let your business―or your career―get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.

Quotes from What to do When Machines do Everything;

“AI isn’t coming; it’s here. What this book attempts to do is show you there are things – many, many things – that you can do – must do – when machines do everything.”

“In this new economy, we will witness an expansion of what is possible and move from machines that do to machines that appear to learn and think.”

“We are using the most powerful innovations since the introduction of alternating current to share cat videos, chat with Aunt Alice and hashtag political rants.”

“Look at your company’s most expensive, premium-level, differentiated products and services. Now imagine them at 10% of the market price.”

“The ‘creative’ forces that machines unleash will be their real legacy.”

“Will some jobs be automated away by AI? Yes, of course. But far more will be enhanced, and in time, millions more new jobs will be discovered, driving future employment.”

5 – User Research | Stephanie Marsh

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Many businesses are based on creating desirable experiences, products, and services for users. However, in spite of this, companies often fail to consider the end-user – the customer – in their planning and development processes. As a result, organizations find themselves spending huge sums of money creating products and services that, quite simply, don’t work. User experience research, also known as UX research, focuses on understanding user behaviors, needs, and motivations through a range of observational techniques, task analysis, and other methodologies.

User Research is a practical guide that shows readers how to use the vast array of user research methods available. Covering all the key research methods including face-to-face user testing, card sorting, surveys, A/B testing, and many more, the book gives expert insight into the nuances, advantages, and disadvantages of each, while also providing guidance on how to interpret, analyze and share the data once it has been obtained.

Ultimately, User Research is about putting natural powers of observation and conversation to use in a specific way. The book isn’t bogged down with small, specific, technical detail – rather, it explores the fundamentals of user research, which remain true regardless of the context in which they are applied. As such, the tools and frameworks given here can be used in any sector or industry, to improve any part of the customer journey and experience; whether that means improving software, websites, customer services, products, packaging, or more.

Quotes from User Research;

“At the inception of the concept, after some initial thinking, you should be doing research to understand whether you are going in the right direction.”

“Involving the right people is one of the fundamentals of doing good research: If you don’t understand who ‘they’ are, you won’t be able to provide ‘them’ with the right thing.”

“Scenarios and storyboards are often combined with personas to put the user at the heart of the design and development process.”

“Throughout the development lifecycle…there will be different methodologies that are appropriate at different times.”

Good content…can help build trust and confidence in users and can reduce the risk of errors being made by your organization and by your users.”

“When you are asking for people’s opinions, make sure you are asking the right kind of questions so as to avoid gathering biased or poor-quality data.”

“When you’re not sure where to focus your test in the beginning, you will be able to narrow down your field of focus in subsequent tests.”

6 – Data-Driven | Tom Chavez, Chris O’Hara, and Vivek Vaidya

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The indispensable guide to data-powered marketing from the team behind the data management platform that helps fuel Salesforce―the #1 customer relationship management (CRM) company in the world.

A tectonic shift in the practice of marketing is underway. Digital technology, social media, and e-commerce have radically changed the way consumers access information, order products, and shop for services. Using the latest technologies―cloud, mobile, social, internet of things (IoT), and artificial intelligence (AI)―we have more data about consumers and their needs, wants, and affinities than ever before. Data-Driven will show you how to:

  • Target and delight your customers with unprecedented accuracy and success
  • Bring customers closer to your brand and inspire them to engage, purchase, and remain loyal
  • Capture, organize, and analyze data from every source and activate it across every channel
  • Create a data-powered marketing strategy that can be customized for any audience
  • Serve individual consumers with highly personalized interactions
  • Deliver better customer service for the best customer experience
  • Improve your products and optimize your operating systems
  • Use AI and IoT to predict the future direction of markets

You’ll discover the three principles for building a successful data strategy and the five sources of data-driven power. You’ll see how top companies put these data-driven strategies into action: how Pandora used second-and third-hand data to learn more about its listeners; how Georgia-Pacific moved from scarcity to abundance in the data sphere; and how Dunkin’ Brands leveraged CRM data as a force multiplier for customer engagement. And if you’re wondering what the future holds, you’ll receive seven forecasts to better prepare you for what may come next. Sure to be a classic, Data-Driven is a practical road map to the modern marketing landscape and a toolkit for success in the face of changes already underway and still to come.

Quotes from Data-Driven;

“We’re increasingly surrounded by a dizzying array of gizmos connected to the Internet…the number of touchpoints that a company can use to engage with us is exploding.”

“Leveraging technology for digital transformation without clear goals is akin to buying a truckload of lumber…and hiring 20 carpenters without an architectural plan.” 

“After years of just talk, marketers are charting data-driven strategies for delivering the right experience to the right person at the right time and the right place.”

7 – Predictive Analytics | Eric Siegel

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In Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, the concept of Predictive Analytics is on a different end of a spectrum. It is a section of computer sciences that consolidates massive data and statistics to predict purchases, candidate choice, and even date of death. It is utilized by different manufacturing, business, health care, law enforcement, and government agencies. Although not entirely perfect, it is more effective than any of the existing hypothesis models. Eric Siegel, the author, has made these engaging, dense, and complex thoughts into a reader-friendly text. Siegel cites real-life examples from famous companies such as Chase Bank, Target, and Hewlett-Packard as he explains his insights as a specialist on Predictive Analytics.

Quotes from Predictive Analytics;

“Organizations are literally keeping kids in school, keeping the lights on and keeping crime down with predictive analytics.”

“Several mounting ingredients promise to spread prediction even more pervasively: bigger data, better computers, wider familiarity and advancing science.”

“Built upon consumer science and statistics and bolstered by devoted conferences and university degree programs, PA has emerged as its own discipline.”

“While prediction itself may be an involved task, it only takes basic arithmetic to calculate the value realized once prediction is working.”

“As the decision tree becomes bigger and more complex, the predictive performance continues to increase, but more gradually.”

“The logical flow of a decision tree amounts to a simple computer program, so, in growing it, the computer is literally programming itself.”

“PA leads within the growing trend to make decisions more ‘data driven,’ relying less on one’s ‘gut’ and more on hard, empirical evidence.”

8 – The Data-Driven Leader | Jenny Dearborn and David Swanson

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Authors Jenny Dearborn and David Swanson grant a continuation of Dearborn’s triumphant masterpiece, Data-Driven. In The Data-Driven Leader: A Powerful Approach to Delivering Measurable Business Impact Through Pople Analytics, the writers concentrate on the implementation of data analytics in human resources.  This continues the tale with a brand new fictional character named Anna. Anna is described to be the HR chief officer of a company that utilized data analytics from an HR point of view to identify and resolve corporate issues. The book details the difficulties, knowledge, graphics, performance indicators, and list that she encountered. This well-written piece is suggested for Data Analysts, HR, Corporate leaders, and students who want to have a more in-depth perception of Data Analytics. 

Quotes from The Data-Driven Leader;

“Moving to a data-driven leadership culture – like any change effort – will bring out the best in some people and the worst in others…find allies early, as detractors may be frequent and fervent.”

“Intuition and emotional intelligence, once the hallmarks of successful chief HR officers and HR professionals, are no longer sufficient.”

“Change takes time and requires the faith and cooperation of mere mortals. This is often truer for cutting-edge advancements like data analytics.”

“CEOs…seeking business leaders to take on the chief HR officer role [value] business acumen – especially experience using analytics to improve business performance – over traditional HR domain knowledge.”

“Too often, human resources leaders talk about ‘soft’ metrics…which are not nearly as compelling to business leaders…as revenue, profitability, customer satisfaction and stock price.”

“Doubling down on what we know, or preferring the status quo to the unknown, may lead us to manage with stale data or ignore indications of shifting metrics or performance drivers.”

“When looking at relationships between KPIs…keep in mind that just because two variables are associated…does not mean we can easily tell which one causes which.”

9 – Big Data in Practice | Bernard Marr

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The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data.

Big data is on the tip of everyone’s tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilize it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective.

From technology, media, and retail, to sports teams, government agencies, and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organized for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved, and the processes put in a place to make it practical, as well as the technical details, challenges, and lessons learned from each unique scenario.

  • Learn how predictive analytics helps Amazon, Target, John Deere, and Apple understand their customers
  • Discover how big data is behind the success of Walmart, LinkedIn, Microsoft, and more
  • Learn how big data is changing medicine, law enforcement, hospitality, fashion, science, and banking
  • Develop your own big data strategy by accessing additional reading materials at the end of each chapter

Quotes from Big Data in Practice;

“Two things…are fueling this big data movement: the fact we have more data on anything and our improved ability to store and analyze any data.”

“Customers can become data-rich with a great many options but insight-poor – with little idea about what would be the best purchasing decision to meet their needs and desires.”

“Any organization without a big data strategy and without plans in place to start using big data to improve performance will be left behind.”

“We are witnessing a movement that will completely transform any part of business and society.

“Humans may not recognize that a certain pattern of activity in the data correlates to a particular likelihood of an event taking place. But if there is a correlation…a computer will be able to spot it.”

“Data is improving our ability to understand and anticipate the effects human activity has on the global wildlife population, and how those changes will inevitably come back to bite us.”

“It’s not a question of whether businesses should be using big data but when and how they should be using it.”

10 – Mind + Machine | Marc Vollenweider

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Evaluserve CEO and Author Mark Vollenweider is an expert in analytics. Part 1 of his manual is a list of analytics-related misconceptions that can help organizations avoid headaches. He later discusses the process of how these can be avoided in part III, as he emphasizes that analytics is functional and sensible. However, given his extensive knowledge in the field, his work can be overwhelming for those who are only beginning to understand analytics. That reason is why this paper is suggested for individuals who have prior knowledge of the topic. Mind + Machine: A Decision Model for Optimizing and Implementing Analytics includes an extensive discussion on the following topics;  Myths on analytics and big data; Stages of data; Data processing; Collection of data; Understanding data;  Digital age; and  Personalization.

Quotes from Mind+Machine;

“For the vast majority of use cases, smarter processes supported by some pretty straightforward tools get you 80% there. AI is the 20% icing on the cake.”

“Knowledge management needs to be purposeful, concrete and action-oriented in order to get the payload delivered.”

“Mind alone is too expensive and too slow. Machine only doesn’t deliver the real insights or knowledge.”

“The underlying drivers for mind+machine approach are fundamentally changing how use cases are conceived, designed, implemented and maintained over their life cycles.”

“The right mix of minds is critical for the success of any mind+machine use case.”

“The increased use of machines to support creative minds is a common characteristic of many alternative and smart data use cases.”

11 – Data-ism | Steve Lohr

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By one estimate, 90 percent of all of the data in history was created in the last two years. In 2014, International Data Corporation calculated the data universe at 4.4 zettabytes, or 4.4 trillion gigabytes. That much information, in volume, could fill enough slender iPad Air tablets to create a stack two-thirds of the way to the moon. Now, that’s Big Data.

Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. The vital raw material of today’s information economy is data.

In Data-ism, New York Times reporter Steve Lohr explains how big-data technology is ushering in a revolution in proportions that promise to be the basis of the next wave of efficiency and innovation across the economy. But more is at work here than technology. Big data is also the vehicle for a point of view, or philosophy, about how decisions will be—and perhaps should be—made in the future. Lohr investigates the benefits of data while also examining its dark side.

Data-ism is about this next phase, in which vast Internet-scale data sets are used for discovery and prediction in virtually every field. It shows how this new revolution will change decision making—by relying more on data and analysis, and less on intuition and experience—and transform the nature of leadership and management. Focusing on young entrepreneurs at the forefront of data science as well as on giant companies such as IBM that are making big bets on data science for the future of their businesses, Data-ism is a field guide to what is ahead, explaining how individuals and institutions will need to exploit, protect, and manage data to stay competitive in the coming years. With rich examples of how the rise of big data is affecting everyday life, Data-ism also raises provocative questions about policy and practice that have wide implications for everyone.

The age of data-ism is here. But are we ready to handle its consequences, good and bad?

Quotes from the Data-ism;

“The age of big data is coming of age, moving well beyond Internet incubators in Silicon Valley, such as Google and Facebook.”

“Data and smart technology are opening the door to new horizons of measurement, both from afar and close-up.”

“Throughout history, technological change has challenged traditional practices, ways of educating people and even ways of understanding the world.”

“Sensing, seeing and acting. That is the promise of big data and it seems straightforward. The improved measure and monitoring that big-data technology makes possible are a kind of seeing.”

Uncertainty and experimentation while pursuing a new set of problems and opportunities are how disciplines emerge in technology.”

“An intensive care unit, as its name suggests, is the epitome of high-stakes medical care, where decisions with life-and-death consequences must be made quickly and frequently.”

“Business intelligence tends to focus on collection, reporting and basic analysis but not on the predictive or experimental features of data science.”

“Online advertising is an economic virtue. It brings…new…efficiency to the market for advertising, reducing costs and freeing money and resources for investment elsewhere.”

12 – What Stays in Vegas | Adam Tanner

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The greatest threat to privacy today is not the NSA, but good-old American companies. Internet giants, leading retailers, and other firms are voraciously gathering data with little oversight from anyone.

In Las Vegas, no company knows the value of data better than Caesars Entertainment. Many thousands of enthusiastic clients pour through the ever-open doors of their casinos. The secret to the company’s success lies in their one unrivaled asset: they know their clients intimately by tracking the activities of the overwhelming majority of gamblers. They know exactly what games they like to play, what foods they enjoy for breakfast, when they prefer to visit, who their favorite hostess might be, and exactly how to keep them coming back for more.

Caesars’ dogged data-gathering methods have been so successful that they have grown to become the world’s largest casino operator, and have inspired companies of all kinds to ramp up their own data mining in the hopes of boosting their targeted marketing efforts. Some do this themselves. Some rely on data brokers. Others clearly enter a moral gray zone that should make American consumers deeply uncomfortable.

We live in an age when our personal information is harvested and aggregated whether we like it or not. And it is growing ever more difficult for those businesses that choose not to engage in more intrusive data gathering to compete with those that do. Tanner’s timely warning resounds: Yes, there are many benefits to the free flow of all this data, but there is a dark, unregulated, and destructive netherworld as well.

Quotes from What Stays in Vegas;

“The best businesses give consumers a choice whether or not to share their data and offer benefits in return.”

“By tracking a gambler’s last visit, a casino has information that can help lure him back in the future.”

“Since the 1990s, a series of start-ups have sought to create tools to help consumers navigate the data-hungry world with greater privacy.”

“Any one piece of data would not reveal very much. But continued advances in data mining have made small bits of personal data ever more revealing when combined – and ever more valuable to companies.”

“Selling other people’s data with or without their knowledge remains far more profitable than protecting and selling data on behalf of consumers, at least for now.”

“The ability to identify people thought to be anonymous has embarrassed well-known companies and institutions that have released data.”

“Large data brokers such as Acxiom buy ethnic data and related software from companies such as Stirista and Ethnic Technologies, making the data widely available to marketers.”

13 – Big Data | Vikto Mayer-Schonberger and Kenneth Cukier

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It 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. Whether it is used by the NSA to fight terrorism or by online retailers to predict customers’ buying patterns, big data is a revolution occurring around us, in the process of forever changing economics, science, culture, and the very way we think. But it also poses new threats, from the end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior. What we have already seen is just the tip of the iceberg.

Big Data is the first major book about this earthshaking subject, with two leading experts explaining what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards.

Quotes from Big Data;

“Big data is all about seeing and understanding the relations within and among pieces of information that, until very recently, we struggled to fully grasp.”

“The scarcity of data is no longer the characteristic that defines our efforts to interpret the world.”

“Things really are speeding up. The amount of stored information grows four times faster than the world economy, while the processing power of computers grows nine times faster.”

“Ultimately, big data marks the moment when the ‘information society’ finally fulfills the promise implied by its name.”

“The important question, however, is not whether big data increases the risks to privacy (it does), but whether it changes the character of the risk.”

“Changes in the way we produce and interact with information lead to changes in the rules we use to govern ourselves, and in the values society needs to protect.”

“Knowing why might be pleasant, but it’s unimportant for stimulating sales. Knowing what, however, drives clicks.”

14 – Taming the Big Data Tidal Wave | Bill Franks

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You receive an e-mail. It contains an offer for a complete personal computer system. It seems like the retailer read your mind since you were exploring computers on their website just a few hours prior….

As you drive to the store to buy the computer bundle, you get an offer for a discounted coffee from the coffee shop you are getting ready to drive past. It says that since you’re in the area, you can get 10% off if you stop by in the next 20 minutes….

As you drink your coffee, you receive an apology from the manufacturer of a product that you complained about yesterday on your Facebook page, as well as on the company’s web site….

Finally, once you get back home, you receive notice of a special armor upgrade available for purchase in your favorite online video game.  It is just what is needed to get past some spots you’ve been struggling with….

Sound crazy? Are these things that can only happen in the distant future? No. All of these scenarios are possible today! Big data. Advanced analytics. Big data analytics. It seems you can’t escape such terms today. Everywhere you turn people are discussing, writing about, and promoting big data and advanced analytics. Well, you can now add this book to the discussion.

What is real and what is hype? Such attention can lead one to the suspicion that perhaps the analysis of big data is something that is more hype than substance. While there has been a lot of hype over the past few years, the reality is that we are in a transformative era in terms of analytic capabilities and the leveraging of massive amounts of data. If you take the time to cut through the sometimes-over-zealous hype present in the media, you’ll find something very real and very powerful underneath it. With big data, the hype is driven by genuine excitement and anticipation of the business and consumer benefits that analyzing it will yield over time.

Big data is the next wave of new data sources that will drive the next wave of analytic innovation in business, government, and academia. These innovations have the potential to radically change how organizations view their business. The analysis that big data enables will lead to decisions that are more informed and, in some cases, different from what they are today. It will yield insights that many can only dream about today. As you’ll see, there are many consistencies with the requirements to tame big data and what has always been needed to tame new data sources. However, the additional scale of big data necessitates utilizing the newest tools, technologies, methods, and processes. The old way of approaching analysis just won’t work. It is time to evolve the world of advanced analytics to the next level. That’s what this book is about.

Taming the Big Data Tidal Wave isn’t just the title of this book, but rather an activity that will determine which businesses win and which lose in the next decade. By preparing and taking the initiative, organizations can ride the big data tidal wave to success rather than being pummeled underneath the crashing surf. What do you need to know and how do you prepare in order to start taming big data and generating exciting new analytics from it? Sit back, get comfortable, and prepare to find out!

Quotes from Taming The Big Data Tidal Wave;

“Perhaps nothing will have as large an impact on advanced analytics in the coming years as the ongoing explosion of new and powerful data sources.”

“Analysts have been pushing the limits of scalability for decades. Big data is just the next generation of intimidating data to tame.”

“A great analysis will be guided by a business need. It won’t be an analysis done just because it is interesting or fun.”

“Big data is sprouting up everywhere, and using it appropriately will drive competitive advantage.”

“It is crucial to understand the difference between statistical significance and business importance.”

“Time and location data is one of the most privacy-sensitive types of big data.”

15 – Search | Stefan Weitz

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Search is as old as language. There has always been a need for one to find something in the jumble of human creation. The first web was nothing more than passing verbal histories down the generations so others could find and remember how not to get eaten; the first search used the power of written language to build simple indexes in printed books, leading to the Dewey Decimal system and reverse indices in more modern times.

Then digital happened. Besides having profound societal impacts, it also made the act of searching almost impossibly complex for both engines and searchers. Information isn’t just words; it is pictures, videos, thoughts tagged with geocode data, routes, physical world data, and, increasingly, the machines themselves reporting their condition and listening to others.

Search: How the Data Explosion Makes Us Smarter holds up a mirror to our time to see if search can keep up. Author Stefan Weitz, a Director in Search for Bing (Microsoft), explores the idea of access to help readers understand how we are inventing new ways to access data through devices in more places and with more capabilities. We are at the cusp of imbuing our generation with superpowers, but only if we fundamentally rethink what search is, how people can use it, and what we should demand of it.

Quotes from Search;

Since we humans first began dreaming of extending our capabilities and leaving the planet – or even our humdrum daily lives – machines have been at the heart of the excursion.”

“The digital utopia that the next generation of search promises to usher in is in no way a done deal.”

The world is racing toward mass digitization, but the technology industry can do more to encourage a higher-fidelity world in less time.”

“Today, consumers have no real way of understanding what their information is worth.”

“There are a number of systems that allow for digitization of the real world in ways that add a higher layer of fidelity to temporal events.”

“Search, in its enlightened form, has the potential to be the hinge that finally connects humanity with machines in a way that lets us transcend our biological limitations.”

16 – Behind Every Good Decision | Piyanka Jain and Puneet Sharma

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Penned by expert data scientists Puneet Sharma and Piyanka Jain, Behind Every Good Decision: How Anyone Can Use Business Analytics to Turn Data into Profitable Insight offers a sharp and well-thought-out guide on Data Analysis. It offers multiple real-life case studies and a list of the most desirable practices. The authors claim that the fundamentals of Analytics that can be done in Excel can solve 80% of business-related issues as long as it is done right. This result can be achieved even by nonanalytic experts such as marketers and managers. People who have an interest in this topic will surely appreciate this book. Still, for those who do not, you can skip to chapter five, where predictive analytics can be found.

Quotes from Behind Every Good Decision;

“Simple analytics can actually help you solve 80% of your business problems at a fraction of the cost of complex analytics.”

“Unless analytics drives business impact, it is not analytics. It is just statistics.”

“Analytics is the science of applying a structured method to solve a business problem using data and analysis to drive impact.”

“A successful analyst uses influence and soft skills to build alignment with the stakeholders or business counterparts.”

“Predictive analytics…requires advanced skills and tools, historical data, operationalization, live validation and constant maintenance.”

“Whatever you do, you will have to explain it to people who aren’t as excited or as involved in the analytics as you are.”

17 – The Naked Future | Patrick Tucker

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An app on your phone knows you’re getting married before you do. Your friends’ tweets can help data scientists predict your location with astounding accuracy, even if you don’t use Twitter. Soon, we’ll be able to know how many kids in a kindergarten class will catch a cold once the first one gets sick.

We are on the threshold of a historic transition in our ability to predict aspects of the future with ever-increasing precision. Computer-aided forecasting is poised for rapid growth over the next ten years. The rise of big data will enable us to predict not only events like earthquakes or epidemics but also individual behavior.

Patrick Tucker explores the potential for abuse of predictive analytics as well as the benefits. Will we be able to predict guilt before a person commits a crime? Is it legal to quarantine someone 99 percent likely to have the superflu while they’re still healthy? These questions matter, because the naked future will be upon us sooner than we realize.

Quotes from The Naked Future;

“Big data will shrink, becoming small enough to fit inside a single-push notification on a single user’s phone.”

“A growing percentage of smartphone users voluntarily surrender data about themselves wherever they use geo-social apps.”

“Telemetry is what divides the present from the naked future.”

“The big data present can give retailers a good understanding of your future buying as your future exists right now, but the naked future is always moving.”

“To this day, the fundamental question that drives the so-called climate debate is simply this: What can and cannot be modeled?”

“Netflix, like Amazon, knows that correlations across data sets don’t offer scientific certainty, but they are enough for sales.”

“One of the fundamental flaws of the big data present, as opposed to the naked future, is that the value or benefits of sharing data is experienced collectively, but the risk is experienced personally.”

18 – Think Bigger | Mark van Rijmenam

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Big data–the enormous amount of data that is created as virtually every movement, transaction, and choice we make becomes digitized–is revolutionizing business. Offering real-world insight and explanations, this book provides a roadmap for organizations looking to develop a profitable big data strategy…and reveals why it’s not something they can leave to the I.T. department.

Sharing best practices from companies that have implemented a big data strategy including Walmart, InterContinental Hotel Group, Walt Disney, and Shell, Think Bigger covers the most important big data trends affecting organizations, as well as key technologies like Hadoop and MapReduce, and several crucial types of analyses. In addition, the book offers guidance on how to ensure security, and respect the privacy rights of consumers. It also examines in detail how big data is impacting specific industries–and where opportunities can be found.

Big data is changing the way businesses–and even governments–are operated and managed. Think Bigger is an essential resource for anyone who wants to ensure that their company isn’t left in the dust.

Quotes from Think Bigger;

“Everything digital is data.”

“The more data that is collected, the better your big data strategy works.”

“The big data era will require employees with different skills doing jobs that until recently did not exist.”

“To truly take advantage of big data, your organization needs to become an information-centric company.”

Final Thoughts

Big data has transformed the world. With the ever-increasing use of technology, faster computers and inexpensive memory, cameras, and sensors fuel big data. Big data allows innovation to flourish and create new business opportunities. Big data increases viable answers and proves value. The list of the best books on big data is a compilation of lists exclusively by the author and the author’s opinions.

Do you see a book that you think should be on the list? Let us know your feedback here.

This page may contain affiliate links. This website may contain content that comes from Amazon. This website and its pages are not intended to constitute legal, financial, or tax advice. The information on this website and its pages are not intended to constitute investment advice and all content are the views and opinions of the author(s), contributors, or administrators. Please read our disclaimer for more info.

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James Gheen

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