There are countless Analytics courses, tutorials, articles available online, but for some, having a book is still a necessity to learn. This is an up-to-date list of recommended books.
1. 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. This guide also helps you understand the many data-mining techniques in use today.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….
2. Analytics: How to Win with Intelligence (2017)
Learn how big data and other sources of information can be transformed into valuable knowledge – knowledge that can create incredible competitive advantage to propel a business toward market leadership. Learn through examples and experience exactly how to pick projects and build analytics teams that deliver results. Know the ethical and privacy issues, and apply the three-part litmus test of context, permission, and accuracy. Without a doubt, data and analytics are the new source of competitive advantage, but how do executives go from hype to action?…
3. 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. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and…
4. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (2016)
“Mesmerizing & fascinating…” “The Freakonomics of big data.” , founding executive of Advertising.com In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement,…
5. HBR Guide to Data Analytics Basics for Managers (HBR Guide Series) (2018)
Today’s business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data–to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?Whether you’re working with data experts or running your own tests, you’ll find answers in the . This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.You’ll learn how to:Identify the metrics you need to…
6. Business Analytics: Data Analysis & Decision Making (2014)
Customized for Paul Damien at the University of Texas at Austin….
7. Predictive Analytics For Dummies, 2nd Edition (2016)
You don’t need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast. With the help of this friendly guide, you’ll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. In no time, you’ll learn how to incorporate algorithms through data models, identify similarities and relationships in your data, and predict the future through data classification. Along the way, you’ll develop a roadmap by preparing your…
8. Business Analytics (2nd Edition) (2015)
teaches the fundamental concepts of the emerging field of business analytics and provides vital tools in understanding how data analysis works in today’s organizations. Students will learn to apply basic business analytics principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. Included access to commercial grade analytics software gives students real-world experience and career-focused value. Author James Evans takes a balanced, holistic approach and looks at business…
9. Marketing Analytics: Data-Driven Techniques with Microsoft Excel (2014)
Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today’s busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Improve your marketing…
10. Business Analytics (3rd Edition) (2019)
For undergraduate or graduate business students. teaches the fundamental concepts of modern business analytics and provides vital tools in understanding how data analysis works in today’s organizations. Author James Evans takes a fair and comprehensive, approach, examining business analytics from both descriptive and predictive perspectives. Students learn how to apply basic principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. And included access to…
Best Analytics Books That You Need
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 Genesis and download some analytics 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.
Analytics Stories: Using Data to Make Good Things Happen
Author(s): Wayne L. Winston
Publisher: Wiley, Year: 2021, Size: 14 Mb, Download: pdf
ID: 2672802
Foundations of Deep Reinforcement Learning: Theory and Practice in Python
Author(s): Graesser, Laura;Keng, Wah Loon
Publisher: Addison-Wesley Professional, Year: 2020;2019, Size: 24 Mb, Download: epub
ID: 2692976
Blockchain in Data Analytics
Author(s): Mohiuddin Ahmed (Editor)
Publisher: Cambridge Scholars Publishing, Year: 2020, Size: 4 Mb, Download: pdf
ID: 2794611
Data Analytics for Engineering and Construction Project Risk Management
Author(s): Ivan Damnjanovic, Kenneth Reinschmidt
Publisher: Springer International Publishing, Year: 2020, Size: 12 Mb, Download: pdf
ID: 2407568
Cyber Security Intelligence and Analytics
Author(s): Zheng Xu, Kim-Kwang Raymond Choo, Ali Dehghantanha, Reza Parizi, Mohammad Hammoudeh
Publisher: Springer International Publishing, Year: 2020, Size: 68 Mb, Download: pdf
ID: 2407727
Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making: Proceedings of the INFUS 2019 Conference, Istanbul, Turkey, July 23-25, 2019
Author(s): Cengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
Publisher: Springer International Publishing, Year: 2020, Size: 60 Mb, Download: pdf
ID: 2408909
Advances in Decision Sciences, Image Processing, Security and Computer Vision: International Conference on Emerging Trends in Engineering (ICETE), Vol. 1
Author(s): Suresh Chandra Satapathy, K. Srujan Raju, K. Shyamala, D. Rama Krishna, Margarita N. Favorskaya
Publisher: Springer International Publishing, Year: 2020, Size: 74 Mb, Download: pdf
ID: 2408948
Google BigQuery: The Definitive Guide: Data Warehousing, Analytics, and Machine Learning at Scale
Author(s): Valliappa Lakshmanan; Jordan Tigani
Publisher: O’Reilly Media, Year: 2020, Size: 6 Mb, Download: epub
ID: 2432389
Computing Predictive Analytics, Business Intelligence, and Economics: Modeling Techniques with Startups and Incubators
Author(s): Cyrus F. Nourani
Publisher: Apple Academic Press, Year: 2020, Size: 12 Mb, Download: pdf
ID: 2434183
Please note that this booklist is not definite. Some books are absolutely record-breakers according to Los Angeles Times, others are composed by unknown writers. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant links you could recommend? Drop a comment if you have any feedback on the list.