Reviews
On Jul 30 Rich Hephner wrote: Too Simple for Some, Not Enough for Others
I got this book expecting something to help me understand data science and maybe be able to converse intelligently with real data scientist at cocktail parties. Instead, it really just focuses on analytical thinking, things that most data scientist would be bored with. Full Review >
Rating:
2.0
On Mar 7 Dallas Marks wrote: A small but terribly helpful soft skills guide for analysts and data scientists
The book provides a framework for defining the problem to be solved, not just "what can we do with this pile of data". In just six chapters and 94 pages, Thinking with Data: How to Turn Information into Insights by Max Shron, a data scientist, fills in several pieces in the process of creating insights from data. Because I'm a consultant, I wish that the book had one or two pictorial visualizations of the author's methodology and some proposed templates or worksheets for deliverables. But this book puts into words something that I often felt was missing from my own requirements gathering and I'm looking forward to writing my first CoNVO. Analysts and designers will find a lot to like in this book. Read it with a highlighter in hand. Full Review >
Rating:
5.0
On Feb 27 Koen Verbeeck wrote: Thinking with Data by Max Shron
A nice introduction to a methodology to tackly data science projects. This book uses various fields such as philosophy, statistics and mathematics to convince the reader to stop and think about the why before the how. A recommended read for data professionals. Full Review >
Rating:
4.0
On Feb 10 Mary Anne Thygesen wrote: Math and Philosophy meets data science
Very useful book like Elements of Style for data science. Math and Philosophy meets data science. There is no code in this book. It is worth reading because it goes over the concepts concisely. Full Review >
Rating:
5.0
On Feb 9 Sumit Bisht wrote: Practical, Precise and Persistant towards finding the right question to be asked
This book specifies what questions to be asked, factors to understand and take account of before proceeding towards solving any big data problem as the tools and algorithms are plentiful but a lot of failed efforts point towards lesser research on selecting a data analysis strategy.
Definitely a read and a companion for reaffirmation for people interested towards solving and improving big data challenges. Full Review >
Rating:
4.0
