12 Data Analytics Books for Beginners: A 2024 Reading List

Written by Coursera Staff • Updated on

Stay up to date with the languages, trends, and ideas permeating the field of data analytics, and add these data analytics books to your reading list.

[Featured image] Man reading book sitting on stairs

We can find data all around us, and the amount of new data available grows daily. So is the demand for skilled data professionals. When taking your first steps towards a career as a data analyst, books can help you learn the terms, key ideas, and concepts popular in the field.

We’ve curated a list of data analysis books for beginners on various topics, from general overviews to topical selections on statistical programming languages, big data, and artificial intelligence (AI). Add these books to your reading list to help you:

  • Assess whether a data analyst career would be a good fit for you

  • Familiarise yourself with the vocabulary and concepts of data analytics

  • Get job advice and prepare talking points for interviews

  • Stay atop the latest data trends

  • Learn new data analyst skills to launch or advance your career

Bookmark this page now to revisit it during your data analytics journey.

Books about data analytics for beginners

You’ll find no shortage of excellent books on data analytics, but we’ve decided to focus on the most relevant for beginners. Many of these titles offer an introduction or overview of a topic rather than a technical deep dive. Some more skills-based books include exercises to get you practising real-world data skills.

1. Data Analytics Made Accessible by Dr. Anil Maheshwari

Best data analytics overview

The chapters in this book are organised much like an introductory college course. Many universities have adopted it as their textbook. It’s an excellent introduction if you’re just getting started in data analytics or wondering what it is all about. Besides high-level overviews of key data concepts, the book also includes:

  • Real-world examples of data analysis in practice 

  • Case study exercises that could lead to potential portfolio pieces 

  • Review questions to help you check your comprehension 

  • R and Python data mining tutorials for complete beginners

Whilst initially published in 2014, the book has gone through several updates (including in 2022) to cover increasingly essential topics like data privacy, big data, artificial intelligence, and data science career advice.

2. Numsense! Data Science for the Layman: No Math Added by Annalyn Ng and Kenneth Soo

Best data science overview

Reading this book provides a gentle immersion into the world of data science—perfect for someone from a non-technical background. The authors walk you through algorithms using clear language and visual explanations so you don’t get bogged down in complex math.

The book offers value to practising data scientists, while it is geared toward beginners. Use it as a refresher on communicating your work to business partners.

3. Python for Everybody: Exploring Data in Python 3 by Dr. Charles Russell Severance

Best book to learn Python

If you’ve never written a line of code before (or still consider yourself a beginner), this book will have you writing your first program in minutes. Dr. Charles Severance of the University of Michigan in the United States walks readers through learning to “speak” to a database through Python.

It’s a helpful resource on its own and even more valuable when used alongside Dr. Severance's popular course, Python for Everybody (available on Coursera).


4. SQL QuickStart Guide: The Simplified Beginner's Guide to Managing, Analyzing, and Manipulating Data With SQL by Walter Shields

The best introduction to SQL

This is so much more than a book. When you buy this book on Structured Query Language (SQL), you get access to a sample database and SQL browser app to put what you’re learning into action immediately. You’ll also get lifetime access to various digital tools—workbooks and reference guides—to complement your learning.

This book covers topics like:

  • Database structures

  • How to use SQL to communicate with relational databases

  • Key SQL queries to complete common data analysis tasks

  • Advice on how to promote your new SQL skills to potential employers

Read more: 4 SQL Certifications for Your Data Career in 2023

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

Best big data book

Whether or not you’re involved in data analytics, you’ve probably heard the term “big data” at some point. This book by two experts in the field goes beyond the buzzword to illuminate how big data is already changing our world for better—and sometimes worse.

This isn’t a technical text to teach you big data algorithms. It’s more of a primer on what big data is, what it can do, and how it might impact the future.

Read more: What Is Big Data Analytics? Definition, Benefits, and More

6. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking by Foster Provost and Tom Fawcett

Best business analytics book

This book digs deep into the importance of data for business decision-making. If you’re interested in pursuing a career as a business analyst, consider this an introduction to how data science and business work together and what goes into data-driven decision-making. 

The authors do an excellent job outlining data science techniques and principles as they relate to business without getting caught up in the technical details of algorithms.

Honourable mention: Too Big to Ignore: The Business Case for Big Data by Phil Simon

7. Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell

Best artificial intelligence book

By reading this book, you can start to separate the hype surrounding the idea of artificial intelligence (AI) from reality. Author Melanie Mitchell, a computer scientist, explores the history of AI and the people behind it to help readers better understand complex concepts like neural networks, natural language processing, and computer vision models.

Whilst data analysts don’t necessarily need a deep understanding of AI, it can be helpful to understand these technologies and their impact on the world of data analytics. Mitchell approaches these topics clearly and engagingly.

8. Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic 

Best data visualisation book

In data analysis, our data is often only as good as the stories we tell with it. This book walks you through the fundamentals of communicating with data through storytelling and visualisation. It combines theory with real-world examples to help you:

  • Recognise context

  • Choose the correct visualisation for the right situation

  • Eliminate clutter and highlight the most essential parts of the data

  • Think like a visual designer

  • Build presentations using multiple visuals to tell a compelling story

Reading this book won’t teach you to create masterful visualisations using R or Tableau, but its insights can equip you to use those tools more effectively when you do learn them. 

9. The Hundred-Page Machine Learning Book by Andriy Burkov

Best machine learning book

This title delivers on its promise: an overview of machine learning in about 100 pages (140 to be exact). It’s short enough to read in a single sitting. Andriy Burkov offers a solid introduction to the field, even if you have no statistical or programming experience. 

This compact read covers an immense amount of information. Topics include supervised and unsupervised learning, neural networks, and cluster analysis. If you’re unfamiliar with those terms, don’t worry—you will be after reading this book. You can always turn to the companion wiki for recommendations on further reading and resources. 

10. Business unIntelligence: Insight and Innovation beyond Analytics and Big Data by Dr. Barry Devlin

Best business intelligence book

This book explores how the trinity of people, processes, and information come together to drive business success in the modern world. This is not a book about traditional business intelligence (BI) concepts. Instead, it outlines how BI can fall short and presents new models and frameworks to improve the practice.

If you’re looking for an overview of BI's past, present, and future, give this book a try. 

Topics discussed include:

  • The birth of the biz-tech ecosystem

  • Practical tips for using big data

  • Data-based, intuitive, and collaborative decision-making (and why companies need all three)

11. Naked Statistics: Stripping the Dread from the Data by Charles Wheelan

Best statistics book

Pick up this book if you need a refresher on what you learnt in college statistics. Pick up this book if you struggle with mathematical concepts presented as a series of numbers and symbols stripped of context. 

Charles Wheelan dives into key concepts in statistical analysis—correlation, regression, and inference—in an enlightening and entertaining way. Wheelan makes a good (and humourous) case for why everyone should understand statistics in our modern world, not just data professionals. 

You may not walk away with a mastery of statistics. Still, this book can help you understand the underlying concepts and why they matter, making it an excellent companion to more technical statistical coursework.

12. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O'Neil

Best book on data bias

Big data can be a powerful tool, and this book serves as a warning and reminder that we must use it responsibly. Data scientist and mathematician Cathy O'Neil explores the consequences of machines making decisions about our lives and how the algorithms driving those decisions often reinforce discrimination. 

Even if you disagree with the author, you might walk away with a better understanding of the darker side of data. These relevant and urgent insights are crucial for those just getting started in the world of data—those who may be tasked with ensuring that future data is used for the benefit of all, not just the privileged. 

Honourable mention: Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Umoja Noble

Get started in data analytics

If you’re interested in data analysis and ready to take the next step towards a career in the field, get started for free with the Google Data Analytics Professional Certificate. Learn what a data analyst does and get an introduction to R programming in as little as six months. Skills you can gain through this programme include data visualisation, data collection, and data ethics.

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