Thinking with Data: How to Turn Information into Insights, by Max Shron

As the emerging field of data science permeates many domains inclusive of information security and privacy, understanding the process of turning information into insights continues to be a major endeavor. In this book, Max Shron provides a practice-oriented set of guidelines, which is geared towards expanding the soft skills required for making the most out of the data. As a data strategy consultant, Mr. Shron acknowledges the importance of hard skills such as data cleaning, mathematical modeling, and data visualization; however, he notes that the soft skills have been ignored within the data science field. He emphasizes that these soft skills, which include “translating vague problems into precisely answerable ones, and combining multiple lines or arguments into one useful result,” can be adapted from other disciplines. The author organizes the book into six chapters. Chapter 1 deals with problem scoping and introduces the readers to a practical framework called CoNVO, which stands for context, need, vision, and outcome. Chapter 2 focuses on techniques to refine the original vision and elaborates on the scaffolding strategy, which is geared toward the initial exploration of data to ensure proper understanding of the problem on hand. Chapter 3 deals with building and presenting arguments, while Chapter 4 discusses three groups of reasoning patterns, which facilitate the structuring of useful arguments. Chapter 5 is dedicated to causal reasoning, whereas the final chapter synthesizes the materials covered from Chapter 1 to 5. The author concludes the book with an appendix dedicated to reading materials, which can be used to further investigate the concepts discussed within the book. In the upcoming paragraphs, I will provide a review of the key ideas discussed in each chapter and conclude my review.