Here's 17 Data Analytics books we recommend every serious Data Analyst reads. Trust us when we say these books are a must-read – as the best-selling authors of Ace the Data Science Interview and creators of Data Analytics Interview Practice Platform DataLemur we've read many Data Analytics books and these truly are the 17 best books on Statistics, SQL, Business Analytics, and Job Hunting out there for Data Analysts.
The 3 best books to learn Data Analytics are Advancing Into Analytics for people who know Excel well, R for Data Science for a practical introduction to Data Analytics in R, and Data Science for Business to learn how data analytics is applied to solve real-world business problems.
If your a new Data Analyst, and you don’t have any programming experience but are handy at Excel, Advancing Into Analytics by George Mount is the perfect gentle introduction to using R & Python for analytics. By covering fundamental concepts in Excel first, and then showing how they directly translate into a programming language, this book eases you into data analytics making it the best book for beginner Data Analysts.
My only issue with this book is that I do think maybe jumping into Python and R for Data Analysts is too big a leap, when SQL is just a perfectly fine intro into the world of Data Analytics. If you want to start with SQL instead, checkout this free SQL tutorial for Data Analysts.
Don't let the word "Data Science" in the book title for R for Data Science scare you – this book is the perfect hands-on introduction to both Data Science AND Data Analytics. The book does a great job balancing implementation details in R while also giving you a big-picture understanding of the data analytics process. See for yourself - the author graciously made the book free online. One caveat: if you do have previous experience with programming in R, go read Advancing into Analytics first
Data Science for Business is a great conceptual introduction to Data Analytics and Data Science. The authors do a great job showing you how Data Analytics impacts day-to-day business decisions. However, this books lacks practical exercises and code snippets, making it not a great hands-on book to learn Data Analytics. That said, having the correct mental models for Data Analytics is important, and being able to connect high-level data analysis techniques to high-level business problems is a crucial skill, so we do think it's still worth reading for Data Analysts.
The 3 best Statistics books for Data Analysts to read are Naked Statistics for a fun introduction to statistics, How to Lie with Statistics to see how statistics can be manipulated, and Practical Statistics for Data Scientists to really master the statistical foundations on which Data Analytics is built upon.
If you don't know statistics and need a fun way to get started, Data Analysts should read Naked Statistics: Stripping the Dread from the Data by Charles Wheelan. This book doesn't have any complicated math or statistics formulas – instead, it provides you with the high-level intuition behind import statistics concepts like inference, correlation, and linear regression.
Data Analysts yield great power – they can present statistics to support the truth, or corrupt statistics to further their own lies. Every Data Analyst needs to read How to Lie with Statistics understand how journalists, politicians, and uninformed people manipulate statistics to serve their own narratives. Just liked Naked Statistics, this book doesn't have too many statistics formulas or complicated math – instead, it serves as a mental model on how to use statistics well, and guard against its misuse.
For Data Analysts trying to master statistics, Practical Statistics for Data Scientists is a must-read book. This book provides a clear and concise introduction to the fundamental concepts of statistics, and has 50+ code examples in Python and R which demonstrate statistical theory. We LOVE this book, because it makes you a better programmer AND a better statistician at the same time, and you'll easily be able to ace probability and statistics interview questions after reading this book!
The 3 best books for Data Analysts to learn SQL are:
SQL shows up in most Data Analyst job listings, so if you don't know this important skill, Practical SQL: A Beginner's Guide to Storytelling with Data is the best book for Data Analysts to start learning SQL. Written by Anthony DeBarros, a data journalist at the Wall Street Journal, this book has a particular focus on using SQL to extract insights from data which can help you uncover a story. The real-world case studies mimic the day-to-day work Anthony does at WSJ, which makes this book an extremely practical way to learn SQL.
Don't let the name fool you – SQL for Data Scientists is one of the best SQL books specifically geared towards Data Scientists AND to Data Analysts as well. Unlike other books, which cover SQL broadly because they are written for a Database Administrator or Back-end Software Engineer, this book focuses on the subset of SQL skills that data analysts and data scientists use frequently, like joins, window functions, subqueries, and preparing your data for Machine Learning.
While this book isn't exactly for SQL interview prep, I do think it covers 90% of the technical concepts that SQL interviews cover. For a more comprehensive guide on how to get interview ready, read the Ultimate SQL Interview Guide:
Minimum Viable SQL Patterns is an e-book by Ergest Xheblati, a former Business Intelligence Analyst turned Data Architect. I recommend this book to Data Analysts who are trying to take their SQL to the next level. By focusing on the workflows and patterns that repeat themself day-to-day, the book will have you writing clean and efficient code to solve the most common workplace SQL problems you'll encounter.
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The 4 best books for Data Analysts who are trying to land their dream job in Data Analytics are How to Get a Job in Analytics, Ace the Data Science Interview, Build a Career in Data Science, and the Startup of You.
In the e-book How to Get a Job in Data Analytics, author Michael Dillon interviews 40 professionals in the Data Analytics industry on how to break-in. Michael is a Data Analyst for Manchester United, and previously was a poker player and trader, so he's intimately familiar with transitioning into the field.
Ace the Data Science Interview is the best book to prepare for a technical Data Analyst interview. It covers the most frequently-tested topics in data interviews like Probability, Statistics, SQL query questions, Coding (Python), and Business Analytics. With 201 real data science and data analytics interview questions to practice with, this book is a must-read for those trying to land data jobs at FAANG, tech startups, or on Wall Street. It also includes job-hunting advice, such as mistakes Data Analysts make on their resume, and ways to build a Data Analytics portfolio project to show recruiters and hiring managers you're a good fit.
Of course, we wrote this Amazon Best-Seller, so we’re a tiny bit prejudiced!
If you're looking for the eBook of Ace the Data Science Interview, we're sorry to announce that there aren't any online PDF or Kindle downloads of Ace the Data Science Interview available. However, you can read many of the SQL interview tips in my 5,000-word SQL interview guide. You can also solve many of the data interview questions from the book are on DataLemur - a SQL & Data Science interview platform. For example, you'll find 100+ SQL Interview Questions from FAANG on there to practice with!
Switching to a career in data isn't easy, but the book Build a Career in Data Science makes things much easier. This comprehensive guide covers the ins and outs of a Data Analytics career – from everything about what to study for Data Analytics and Data Science, to how to job hunt effectively, to what it takes to succeed in your first few Data Analytics roles. Be warned: the detailed nature of this book might dishearten you, once you realize how much time and effort you need to make this career move. Then again, if Data Analytics was easy, everyone would be doing it!
Drawing on the best career advice Silicon Valley has to offer, the book "The Startup of You" helps you think of your Data Analytics career in a more entrepreneurial and scrappy light. Written by Reid Hoffman, Founder of LinkedIn turned VC at Greylock, the book challenges traditional career advice in many places because it argues we no longer live in a world where it's reasonable to work at one company for 30 years and retire with a pension. In today's fast-moving world of Data Analytics & Technology, there's a new set of rules for career success, and the Startup of You explains exactly how to transform your career in this new age.
The 3 books we recommend Data Analysts read to improve their business skills are the Personal MBA, On Strategy by the Boston Consulting Group, and Lean Analytics.
As a Data Analyst, you'll be closely collaborating with business stakeholders, so it only makes sense you understand more about their world! Otherwise, how can you do a financial analytics project or marketing analytics project, when you don't even know the basics of finance or marketing? That's where the Personal MBA shines, by distilling a 2-year Harvard MBA into something which takes a tiny fraction of the time and money.
On Strategy is written by the top Management Consultants at the prestigious Boston Consulting Group (BCG). You'll learn big-picture concepts like organization design, change management, and developing business strategies! As a Data Analyst, you might find yourself presenting data-driven recommendations to the C-Suite, or doing analysis that informs the company’s larger strategic vision, so having an understanding of the buzzwords and thought process at the top rungs on the ladder will be an invaluable asset.
Lean Analytics is valuable to any Data or Business Analyst who frequently has to define new metrics at their workplace. The book walks through the most important metrics to measure for a variety of tech business models, and talks about what makes a metric good or bad. This book is also an excellent resource for anyone interviewing for a Product Analytics role, because many of the interview questions for those types of jobs can be answered by frameworks found in this book.
Because Data Analytics work closely related to the field of Data Science, you'll also enjoy the suggestions made in our article on 13 must-read books for Data Scientists. There, you'll find some of our top books to learn Data Science, the top books on Machine Learning for Data Scientists, and best Product Management books for Data Scientists.
Nick Singh is a former Software Engineer at Facebook & Google, now turned career coach. His career advice on LinkedIn has earned him over 120,000 followers on the platform. Kevin Huo is a former Data Scientist at Facebook, and now a quant on Wall Street. He's helped coach hundreds of people to land data jobs at Amazon, Two Sigma, and Lyft. Together they wrote the Amazon #1 Best-Seller, Ace the Data Science Interview, which solves 201 real Data Science & Data Analytics interview questions from FAANG, Tech Startups, and Wall Street.
Nick Singh then went on to found DataLemur - an interactive SQL & Data Science Interview platform, that features hundreds of real Data Analyst and Data Science questions from companies like Facebook, Google, and Accenture.
