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, by Thomas H. Davenport Kim,(Professor of business and statistics) Jinho
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Product details
File Size: 2027 KB
Print Length: 241 pages
Publisher: Harvard Business Review Press (May 21, 2013)
Publication Date: May 21, 2013
Sold by: Amazon Digital Services LLC
Language: English
ASIN: B00B0SA1LY
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I loved the style of the authors regarding the basic concepts BUT the examples and stories they tried to relate to... oh my, they were not good. I've had some experience with numbers in my work and this book was for my MBA program. Therefore, I'm not a novice but the book made a point about relating stories to numbers and how effective it is (I agree, of course) but the stories this book tried to tie in were off the mark most of the time. That being said, there are so many good parts of the book to help you develop your quant brain.
I had a little trouble understanding who the authors had in mind as the audience for this book. It seemed to basic for any professional who would have to deal with statistics/data or would have to manage/collaborate with someone who does.There are some helpful reminders throughout about how to approach problems and how to communicate your ideas. But the authors seem seem to replace depth with a multiplicity of business-y anecdotes (ironic, as they include the old chestnut "the plural of anecdote is not data" - the plural of anecdote, it so happens, is not "a book").Overall, the book feels superficial. It might inform you how to probe an analyst on first-level questions, but doesn't provide enough depth to take you through a couple follow-ups or know when you're getting snowed.
As a management professor I keep reading all sorts of books. This book is a nice introduction to Quants for people who are afraid of numbers and data. It is written in simple language and analytic concepts are explained well for non-data people. A good introductory book if you are looking to acquaint yourself with the analytics world!
basically story-telling, too basic, a light introductory work, no takeaways, although some examples presented were interesting. Not for a seasoned professional.
I just took a new position, and my dean has been trying to develop a better decision making process and structure. This book is a must read for anyone not in the data science business but who needs to understand how to use data better and learn what questions to ask and pitfalls to avoid in collecting and using data.It's a very valuable investment of time to read. I promise it will stay on my Kindle forever, and I'll recommend it to anyone who has decision making responsibility.
This is a fine introduction to the world of data analysis for business professionals. The authors do a fine job of providing a generalized framework for analytic approaches to business problems. It also provides a number of helpful anecdotes which are presented in terms of the framework to help the reader understand them as real-world exercises. Other than that, it is a very standard business publication - high on concept, low on practical impacts. If you are already familiar with basic analytic techniques or are a designer or user of BI/dashboards/etc., then this book is not for you. If you are completely new to these things, it will be helpful.
Must read for non-quant managers and analysts involved in business analytics. Author clearly did a good job of explaining problem framing to decision making in easy language. It is also a good read for quant people to understand on how to communicate extracted information to co-worker and managers.
If you aren't a quant but you realize the power and importance of data driven business, this book is for you. A very solid, accessible overview that will get you started. Be sure to read through to the end for a well thought-out, first-of-its-kind guide to working with quants, including expectations management, communication guidelines, etc. -- which is also great for quants as well to help folks understand boths sides of the communication gap and bridge this sometimes cavernous divide.Eric Siegel, Ph.D.Founder, Predictive Analytics WorldAuthor, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die
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