The 6 Best Data Science Books for Non-Techies
Data science is an amazing field to be in right now. The amount of data being produced at technology companies as well as companies in traditional industries is astounding. Many individuals competent in analytical and technical skills are transitioning to the field through graduate programs or immersive bootcamps.
However, not everyone enjoys learning the mathematical basis for Support Vector Machines or how to implement the Logistic Regression algorithm with mini-batch gradient descent. In most cases, you may be a manager, executive or data analyst who works alongside data scientists. You are probably content with your position and have no immediate desire to transition into data science, but want to learn more. Does this sound like you?
Here is the list of the 6 best data science books to read if you want to learn about the use cases for data science and analysis without diving into the nitty-gritty math.
Synopsis: Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.
Synopsis: The topics of big data and analytics continue to be among the most discussed and pursued in the business world today. While a decade ago many people still questioned whether or not data and analytics would help improve their businesses, today virtually no one questions the value that analytics brings to the table. The Analytics Revolution focuses on how this evolution has come to pass and explores the next wave of evolution that is underway. Making analytics operational involves automating and embedding analytics directly into business processes and allowing the analytics to prescribe and make decisions. It is already occurring all around us whether we know it or not.
Synopsis: In this concise book you will learn what you need to know to begin assembling and leading a data science enterprise, even if you have never worked in data science before. You’ll get a crash course in data science so that you’ll be conversant in the field and understand your role as a leader. You’ll also learn how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You’ll learn the structure of the data science pipeline, the goals of each stage, and how to keep your team on target throughout. Finally, you’ll learn some down-to-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.
Synopsis: Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you’re going to click, buy, lie, or die. Predictive Analytics unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.
Synopsis: You may be the owner of a business, or someone who actively participates in the day to day operations of a business. We will go ahead and assume that your business is operating at a profit and you are happy with the direction it is going. As someone in this situation you might ask yourself, “Why do I need Data Analysis anyways?”. I’ll tell you why, one simple reason. You are leaving money on the table. Let’s put it this way.. you are doing good, but wouldn’t you rather be doing great? Wouldn’t you rather have the ability to predict how the consumers in your target market are going to be behaving a year from now? Five years from now? This is where Data Analysis comes in. Many people realize the need to pay attention to data in their business, but have no clue where to start. With the help of this book you will be better able to understand the importance of the data surrounding your business and exactly what to do with it.
Synopsis: The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits makes the case that big data is for real, and more than just big hype. The book uses real-life examples — from Nate Silver to Copernicus, and Apple to Blackberry — to demonstrate how the winners of the future will use big data to seek the truth. Written by a marketing journalist and the CEO of a multi-million-dollar B2B marketing platform that reaches more than 90% of the U.S. business population, this book is a comprehensive and accessible guide on how to win customers, beat competitors, and boost the bottom line with big data.
