Numbersense: How to Use Big Data to Your Advantage

by Kaiser Fung
Numbersense: How to Use Big Data to Your Advantage cover
Good Books rating 4.42
Business and Economics
Buy online
Amazon
Format/Price Check
Technical
  • ID: 10779
  • Added: 2026-02-03
  • Updated: 2026-02-03
  • ISBN: 9780071799676
  • Publisher: McGraw Hill Professional
  • Published: 2013-07-12
  • Reviews: 3

In a world drowning in Big Data, making sense of the numbers is more important than ever. Numbersense: How to Use Big Data to Your Advantage by Kaiser Fung delves into the complexities of data interpretation, offering insights into how we can navigate the sea of information that surrounds us. From college rankings to unemployment statistics, this book explores the ways in which data is collected, analyzed, and often misinterpreted. Fung's expertise in statistics shines through as he provides practical advice on how to approach data with a critical eye, ensuring that you can make informed decisions based on accurate interpretations.

Reviews
Barnes & Noble · 2026-02-03
engaging 4.75

The book is praised for its emphasis on the analysis of big data rather than its size. It is filled with fun stories and valuable lessons learned.

This review from Barnes & Noble highlights the book's unique approach to big data, focusing on the analysis rather than the sheer volume of data. The reviewer enjoys the fun stories and practical lessons that make the book both entertaining and educational. It's noted that the book is a great resource for anyone looking to understand the nuances of big data analysis. The reviewer appreciates the book's ability to make complex topics accessible and engaging.

Quick quotes

    Numbersense correctly puts the emphasis not on the size of big data, but on the analysis of it.

    Lots of fun stories, plenty of lessons learned—in short, a great resource for anyone looking to understand the nuances of big data analysis.

    The book is a great resource for anyone looking to understand the nuances of big data analysis.

Data Innovation · 2013-08-02
informative 4.00

The book provides a clear and accessible introduction to big data analysis, making complex concepts understandable for non-technical readers. It emphasizes the importance of understanding the analysis rather than just the size of the data.

This review highlights how the book effectively breaks down the complexities of big data into digestible insights. The author's approach is praised for making the subject matter engaging and relevant to everyday life. The reviewer appreciates the practical examples and the emphasis on the quality of analysis over the sheer volume of data. It's a great resource for anyone looking to understand the nuances of big data without getting bogged down in technical jargon.

Quick quotes

    In Number Sense, author Kaiser Fung seeks to give nontechnical readers the background they need to understand how big data affects their lives.

    Fung provides a blueprint for dissecting data analysis.

    The book is a follow-up to the 2010 release Numbers Rule Your World.

Eponymous Pickle · 2013-07-08
practical 4.50

The book is a valuable guide for understanding when data analysis is on the right track or going wrong. It offers practical advice on how to navigate the complexities of big data.

This blog post emphasizes the book's focus on developing a 'numbersense'—the ability to discern the quality of data analysis. The reviewer finds the book particularly useful for its practical advice and real-world examples. It's noted that the book doesn't just focus on the size of big data but on the critical analysis of it. The reviewer appreciates the book's ability to make complex topics accessible and engaging.

Quick quotes

    The title of the book NumberSense, is that quality of understanding when an analysis is right or going wrong, and what to do about that.

    The book offers practical advice on how to navigate the complexities of big data.

    It's noted that the book doesn't just focus on the size of big data but on the critical analysis of it.

Appears in Lists