📚 Stop Doing Random Data Courses - Read These Books Instead
Tired of wasting money on your 17th Udemy courses you never finish? These 7 books will actually make you a better analyst—no silly subscription required.
psssst....I'm sending one of YOU a copy of one of these books...read on to find out how.
Get the Books Here
The following are Amazon affiliate links. I might earn a few pennies (at no cost to you), if you end up purchasing any of these books!
1. The Big Book of Dashboards
The Big Book of Dashboards is a must-have. Written by Tableau legends Steve Wexler, Jeffrey Shaffer, and Andy Cotgreave, this book is a perfect blend of practical principles and real-world examples.
The first half covers fundamental data visualization principles: what makes a good graph, how to use color effectively (sequential vs. diverging), and the different types of charts you might use.
The second half dives into 28 practical dashboard examples from various industries—sales, manufacturing, sports, healthcare, and more. Each dashboard is accompanied by:
The business context and key stakeholder needs behind its creation
Suggestions on how to apply the dashboard concepts to other industries
A detailed breakdown of each graph, title, and color choice
Alternate visualization options to remix the dashboard
Author commentary providing insights into the design process
Plus, you get access to all the Tableau files, which means 28 ready-made templates to jumpstart your projects. This book is hands-down worth adding to your collection.
2. Data Science for Business
Data Science for Business by Foster Provost and Tom Fawcett does exactly what the title promises: it bridges data science with business in a meaningful and applicable way. Unlike many books that focus solely on just coding or just business theory, this one balances both worlds.
This book covers:
Data cleaning and databases
Data modeling techniques like regression and classification
Machine learning fundamentals including clustering and text analysis
Ethical considerations and privacy issues
It’s particularly valuable because it reflects the kind of learning you’d experience on the job in a corporate environment, mixing practical applications with essential theory.
For me, this book is the closest thing to learning data "on the job".
3. Fundamentals of Data Engineering
Fun fact: I taught a data engineering boot camp at MIT for a year, and this book was my go-to resource for filling in the gaps in my knowledge.
Fundamentals of Data Engineering by Joe Reis and Matt Housley is a comprehensive, somewhat theoretical guide that feels like a future college textbook. It covers:
What data engineering is and the role of a data engineer
Differences between data lakes and data warehouses
Cloud storage concepts and data querying
Automation, scheduling, and orchestration of data workflows
Popular tools like Kafka, Spark, and Airflow
If you want to understand the infrastructure behind data pipelines and how to build efficient, scalable systems, this book is invaluable.
4. The StatQuest Illustrated Guide to Machine Learning
If you’re a visual learner or find machine learning concepts intimidating, The StatQuest Illustrated Guide to Machine Learning by Josh Starmer (also known as StatQuest) is a gem. Josh is famous for his fun, clear YouTube videos explaining statistics and machine learning with simple illustrations and memorable catchphrases like “triple bam.”
This book compiles his teaching style into a highly illustrated guide that covers:
Linear regression
Decision trees
Neural networks
Support vector machines
And much more
It’s detailed enough to be used as a college textbook, but friendly enough to not bore me to death. If you want a reference book that keeps the fun in learning, this is the one.
5. Moneyball
Yes, it’s a classic and a bit expected, but Moneyball by Michael Lewis is a must-read for anyone interested in how analytics can revolutionize an industry. The story of how the Oakland Athletics, one of the poorest teams in Major League Baseball, used data-driven strategies to compete with richer teams is inspiring.
Instead of focusing on traditional stats like home runs, they looked at metrics like on-base percentage that better predicted winning. This shift not only changed baseball but also demonstrated how to get analytics accepted in organizations resistant to change.
The book also highlights the challenge many analysts face: convincing seasoned experts to trust data over their years of experience. It’s a great lesson in both analytics and organizational change management.
Fun fact: I paid $2,000 for a "Data Business" course in my Master's where we spent half the semester reading this book. Save your money - do The Accelerator instead of a Master's 🤣
I promise we do more than read a $15 book.
6. Ace the Data Science Interview
I'm kinda convinced if you want a FAANG job, you could just read this book 5x and be set.
Written by my friends Nick Singh and Kevin Hua, Ace the Data Science Interview is a fantastic guide for anyone preparing for data science roles, especially at top tech companies like Meta, Google, and others.
The book covers:
Job hunting strategies including cold emails and data projects
Behavioral interview tips
Technical interview preparation focusing on statistics, probability, SQL, coding, product sense, and case studies
If you want to nail the notoriously tough technical interviews at FANG companies, this book will be your secret weapon. It’s practical and targeted, making your prep much more efficient.
7. Storytelling with Data
My personal favorite, Storytelling with Data by Cole Nussbaumer Knaflic, is all about turning your data into compelling stories that drive action. It’s not enough to have great analysis—you need to convince others to act on it.
The book is divided into two parts:
Data visualization principles with step-by-step graph remakes that show how to reduce clutter and use color effectively
Presentation and storytelling techniques to help you communicate your insights persuasively
This is especially helpful when you face skepticism from people who have been doing things a certain way for decades. It teaches you how to use visuals and narrative to break through resistance and make your analytics count.
Bonus: Win a Free Book
As a way of saying thank you for being subscribed to my newsletter, I want to give one of you a free copy of Storytelling with Data to one lucky reader anywhere in the world.
To enter, simply subscribe to my newsletter at datacareerjumpstart.com/newsletter (or do nothing if you're already subscribed there).
Rules? Randomly chosen, but weighted by how active you are. The more you open my emails, click on links, and reply, the better chance you'll have. Feel free to click all these links and reply to this email to boost your odds (lol).
I’ll announce the winner at the end of the month.
May the odds be ever in your favor!
