Title: Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Author: Martin Kleppmann
Title: Build a Large Language Model (From Scratch), Author: Sebastian Raschka
Title: Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter, Author: Wes McKinney
Title: Murach's Python for Data Science (2nd Edition): Training and Reference, Author: Scott McCoy
Title: Fundamentals of Data Engineering: Plan and Build Robust Data Systems, Author: Joe Reis
Title: R for the Rest of Us: A Statistics-Free Introduction, Author: David  Keyes
Title: From Numbers to Narratives that Transform Businesses: Harnessing the Power of Data Visualization, Author: Joe Perez
Title: Cybersecurity Tabletop Exercises: From Planning to Execution, Author: Robert Lelewski
Title: Data Science from Scratch: First Principles with Python, Author: Joel Grus
Title: R for Data Science: Import, Tidy, Transform, Visualize, and Model Data, Author: Hadley Wickham
Title: Data Visualization with Python and JavaScript: Scrape, Clean, Explore, and Transform Your Data, Author: Kyran Dale
Title: Data Visualization with Microsoft Power BI, Author: Alex Kolokolov
Title: Thematic Mapping: 101 Inspiring Ways to Visualise Empirical Data, Author: Kenneth Field
Title: Definitive Guide to DAX, The: Business intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel, Author: Marco Russo
Title: Data Engineering Design Patterns: Recipes for Solving the Most Common Data Engineering Problems, Author: Bartosz Konieczny
Title: Learning Google Analytics: Creating Business Impact and Driving Insights, Author: Mark Edmondson
Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Author: Trevor Hastie
Title: Learning Microsoft Power BI: Transforming Data into Insights, Author: Jeremey Arnold
Title: SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights, Author: Cathy Tanimura
Title: Murach's R for Data Analysis, Author: Scott McCoy

Pagination Links