Data Analytics, Data Visualization & Communicating Data: 3 books in 1: Learn the Processes of Data Analytics and Data Science, Create Engaging Data ... Present Data Effectively (All Things Data) Paperback – 10 Nov. 2022

Overall, "Data Analytics, Data Visualization & Communicating Data: 3 books in 1" is a comprehensive guide to understanding and working with data in various capacities. The three books in the series cover a range of topics, including an overview of the data collection and management processes, the fundamentals of cleaning data and using machine learning algorithms for analysis, and an in-depth look at data visualization and how to present data effectively.The book us well-suited for beginners looking to gain foundational knowledge in the field of data science and those looking to transition into a data-related career. The range of topics covered and the emphasis on practical skills make this book a valuable resource for those seeking to improve their data literacy and set themselves up for success in the rapidly growing field of data science.

I found this book great value, for the scope of the material covered.

This book is a useful foundation for anyone getting into data analysis and visualisation. While it wasn't exactly what I wanted, level wise, it's a nice book to have if you ever want to revise the fundamentals. Yes there is probably web resources you can get for free or less but I'm old fashioned and I like a book to read sometimes.

This book is compact and rich with content that most data analytics professionals would value or people with an interest in data. There's an awful lot covered here but I'll jump straight to what tickles my fancy which is the storytelling & getting the narrative right.Having been a consultant before a common challenge is often how you position your analysis and narrative so it's consumable for your clients and sponsors. This author simplifies this challenge and provides some good examples and structure to follow (hooks, the what, who & how) which is very practical & a win-win . A must-have for any data science library