In a world driven by data, data science is quickly growing beyond all the challenges in the future, and it has now become the sixth sense. Educating yourself using data science books is a holistic approach to gaining data skills, problem-solving, programming, analyzing trends, and predicting their impact on your business. Below is a list of the top 10 must-read books for the data-driven executive.
1. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by E. Siegel
Some of the most prominent business intelligence trends include predictive analytics, which holds power to unleash big data’s power. Companies employ predictive analytics to understand their products, their companies, and their competitors. By analyzing this data, they can effectively identify potential opportunities and risks for the company. It is not a cheap ploy to make sales but rather a technological leap that utilizes data analytics to predict human behavior, which is crucial in crime-fighting, improving health, reducing spam, combat financial risk, and boost sales.
2. Too Big to Ignore, by P. Simon
This book explores how companies and local governments use big data to their advantage, such as progressive insurance’s use of GPS trackers to determine safety ratings. Local governments fix a problem using the data residents’ input to their smart gadgets, and Google’s ability to predict an outbreak through the local searches. Big data as a part of data science is not a fad, and Too Big to Ignore, teaches you what big data can do for you and your business and how you can make the most of this innovation.
3. Black Box Thinking, by Matthew Syed
Failure occurs in each field of life, and you will have to experience it from time to time. However, for individuals working in sensitive sections such as health and aviation, mistakes can have catastrophic consequences. The health sector is responsible for thousands of deaths. However, none of that information is ever made public due to nondisclosure clauses in the malpractice settlements. In aviation, once there is an error, the data in the black box is analyzed, a report publicly made, and changes implemented to the necessary procedures. The book, Black Box Thinking, suggests adopting the latter approach to dealing with mistakes to create an environment where it is okay to fail and eliminate stigma and shame surrounding failure.
4. Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting data, by EMC Education Services
Data science and big data analytics are mostly about harnessing the possibilities of new insights and available data. The content focuses on the activities, methods, and tools that data scientists use during data analytics. Through practical applications, the book illustrates how you can apply these techniques to your environment. This book is critical if you desire to become a contributor to data science, learn to deploy appropriate approaches to data analytics problems, and learn to tell compelling stories using data to drive business action.
5. Data Smart: Using Data Science to Transform Information into Insight, by J. W. Foreman
Using accessible analytic techniques and improving available software can help you achieve progressive success. This book focuses on teaching the few areas where analytic techniques and data can deliver definite benefits. Each chapter delves into a particular method: genetic algorithms, nonlinear programming, graph modularity, clustering, and data mining in graphs and prediction intervals. It details practical information that you can use to start performing data analytics by using regular Microsoft excel. Once you register significant growth and begin dealing with big data with millions of rows and columns, you can turn to self-service business intelligence.
6. Thinking, Fast and Slow, by Daniel Kahneman
In his book, Daniel Kahneman, a renowned psychologist, explains how the two systems govern how you think and process data. Whether it is deciding the next corporate strategies to adopt, where to take your next vacation, your next play on the stock market, your mind uses either of two systems. System one is fast, emotion-based, and intuitive. System two is deliberate, logical, and much slower. The books seek to engage you in a conversation about the two systems that can benefit different scenarios, instances that defeat your intuition, require more logic, and data-based information. It offers enlightening and practical insights into how best to make decisions that affect your organization, and techniques that can help you guard your mind against errors that may lead to poor choices.
7. Big Data: A Revolution That Will Transform How We Live, Work, and Think by V. Mayer-Schönberger and K. Cukier
This book provides a more general outlook on big data’s crucial characteristics and how the technology will advance. Some of these characteristics include; variety, volume, veracity, and velocity. As a business, it is crucial to understand your consumers and effectively predict their needs for successful growth. You can positively impact how your team processes and manages data by the completeness of data, quantifying and digitizing previously inaccessible information, and using statistical tools such as data mining and machine learning.
8. Big Data at Work: Dispelling the Myths, Uncovering the Opportunities, by T. H. Davenport
This book is a must-read for managers that seek to understand big data without the hype surrounding it. It highlights essential skills such as developing an action plan regarding big data, selecting the kind of technology you need, identifying, and hiring the right people to work on big data. It also expounds on the successes and failures of big data technologies that have been adopted by online firms, startups, and large organizations to give a more practical approach to data analytics.
9. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications, by B. Baesens
Analytics in a Big Data World serves as a resource on data analytics techniques that provide significant value in business environments. It is a no-nonsense book that focuses on technical and structural instructions on how you can conduct big data analytics practically and efficiently. It details the entire process involved in data science, such as the basic nomenclature, the process model, essential steps of the process model, and finally, the descriptive and predictive analytics.
10. Lean Analytics, by Alistair Croll & Benjamin Yoskovitz
Marc Anderson once said that the most significant risk is building something nobody wants. The fear of committing your time, energy, and money to something that fails can be daunting. However, this book helps you build your business by using business analytics. It covers more than thirty real-life case studies, which helps give a more practical and realistic approach to building and managing a business, an insight into what works and what doesn’t, and how best to avoid other people’s mistakes.
As a data-driven executive, it is imperative that you stay updated and upskill your talent to stay ahead of your competitors and to lead your teams effectively. These books provide information for various levels to engage beginners and data analysts at advanced levels. They give an insight into how data science translates to your everyday life and how it affects your business.