Best Data Modeling & Design Books of 2025

Designing Data-Intensive Applications is a comprehensive guide to navigating the diverse landscape of data processing and storage technologies. The author, Martin Kleppmann, helps software engineers and architects make informed decisions by examining the strengths and weaknesses of various tools. He also provides insights into the distributed systems research that modern databases are built upon. With practical examples and case studies, this book is a valuable resource for anyone dealing with the challenges of scalability, consistency, reliability, efficiency, and maintainability in data-intensive applications. Overall, this book is a great addition to any data modeling and design bookshelf.

Fundamentals of Data Engineering: Plan and Build Robust Data Systems is a practical guide for software engineers, data scientists, and analysts seeking a comprehensive view of data engineering. The authors, Joe Reis and Matt Housley, walk readers through the data engineering lifecycle, providing an end-to-end framework of best practices for designing and building a robust architecture. Readers will also learn how to evaluate the best technologies available and incorporate data governance and security across the data engineering lifecycle. This book is a valuable resource for anyone looking to navigate the rapidly-growing field of data engineering.

Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street is a must-read guide for anyone who wants to land their dream job in data science, data analysis, or machine learning. Authored by two ex-Facebook employees, this 301-page book offers comprehensive coverage of the most frequently tested topics in data interviews. It provides detailed step-by-step solutions to 201 real data science interview questions asked by top companies, including Facebook, Google, Amazon, Netflix, Two Sigma, and Citadel. Additionally, the book offers valuable career advice on crafting your resume, creating portfolio projects, networking, and more. Overall, Ace the Data Science Interview is an invaluable resource for anyone looking to break into the data science industry.

The Python Programming and SQL: 5 books in 1 is an all-in-one guide for beginners and advanced learners who want to master Python and SQL programming languages. The guide offers step-by-step instructions and practical experience, making it easy for readers to start coding in no time. It covers essential tools, strategies, and real-world applications with easy-to-understand examples and exercises. The book is an excellent resource for anyone looking to learn coding, from basic to advanced levels, and it provides excellent value for money as five books are bundled into one unique guide.

"Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD" is a must-read for programmers who want to achieve impressive results in deep learning with minimal code and math background. Jeremy Howard and Sylvain Gugger, the creators of fastai, provide a hands-on guide to train a model on a wide range of tasks using fastai and PyTorch. The book covers the latest deep learning techniques and provides a complete understanding of the algorithms behind the scenes. Overall, it's an excellent resource that simplifies complex concepts and makes deep learning accessible to everyone.

"Effective XGBoost" is a comprehensive guide to mastering the art of classification using the popular machine learning algorithm, XGBoost. From basic usage to advanced techniques, the book covers everything a data scientist needs to know to become an expert in XGBoost. It includes practical advice, real-world examples, and step-by-step instructions on optimizing, tuning, understanding, and deploying XGBoost models. This book is a must-read for anyone looking to improve their data science skills or working on a Kaggle competition. The clear explanations and expert advice make it an ultimate guide to mastering XGBoost.

Learning SQL: Generate, Manipulate, and Retrieve Data is an essential guide for developers seeking to master SQL fundamentals. With comprehensive coverage of SQL basics and advanced features, the latest edition includes new chapters on SQL and big data, analytic functions, and working with large databases. The author, Alan Beaulieu, delivers self-contained lessons on key SQL concepts and techniques with numerous illustrations and annotated examples. Exercises ensure readers can practice the skills they learn. This book is a must-read for anyone looking to interact with data and put the power and flexibility of SQL to work.

Data Science for Business is a comprehensive guide to understanding data science and its role in business decision-making. Written by experts Foster Provost and Tom Fawcett, this book teaches readers the principles of data-analytic thinking and the various data-mining techniques used today. It includes real-world business examples to illustrate these principles and helps improve communication between business stakeholders and data scientists. The book also provides guidance on how to participate intelligently in data science projects and how to apply data science principles when interviewing data science job candidates. Overall, it is an essential resource for anyone looking to gain a competitive advantage through the use of data.

"SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights" is a practical book that provides new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. It covers both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways. The author, Cathy Tanimura, has over 20 years of experience analyzing data with SQL across most of the major proprietary and open source databases. This book is a must-have reference for anyone who works with SQL databases.

Learning Tableau 2022, 5th Edition, is a comprehensive guide that helps readers understand how to analyze and communicate data visually, and articulate data stories using advanced features. With the latest Tableau 2022 features, readers can harness the full potential of artificial intelligence and predictive modeling in Tableau. From the core principles to creating stunning visualizations, interactive dashboards, and interlinking different data sources, this book covers all the essential aspects of data analysis. Overall, this is an excellent resource for anyone looking to enhance their data storytelling capabilities and make better business decisions.