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Keeping Up with the Quants: Your Guide to Understanding and Using Analytics Kindle Edition

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EUR 13,99

Länge: 241 Seiten Word Wise: Aktiviert Sprache: Englisch



Shortlisted for CMI Management Book of the year award 2013 (New Manager category)

“an accessible and timely introduction to the data mining work of quantitative analysts.” Named it one of “Four Books [that] Should Top Every Marketer’s Summer Reading List.” —

“goes into fascinating detail about how Intel and other successful companies—including Verizon Wireless, TD Bank Group, and Merck—help managers and data scientists understand each other well enough to collaborate effectively.” — CNNMoney/Fortune magazine

“perfect for professionals who want a better grounding in understanding and applying data results to business goals” — Midwest Book Review

“Written for readers without a business degree or background in statistics, Keeping Up With the Quants explains how to read, interpret, and glean value from your data.” — T+D magazine (American Society for Training & Development)

“the book makes for great reading for leaders trying to corral data in their organization.” — Small Business Trends (

“Decision makers who want to understand how to utilize Big Data have a useful primer in Keeping Up with the Quants." — BizEd magazine

“a terrific book for those who aspire to be data-savvy consumers or managers, even for those who might become quants one day themselves.” — Seeking Alpha

ADVANCE PRAISE for Keeping Up with the Quants:

Erik Brynjolfsson, professor, MIT Sloan School of Management; coauthor, Race Against the Machine
“As digital information becomes ever more abundant, quantitative literacy becomes ever more essential. There is no better guide to this new landscape than Keeping Up with the Quants.”

Daryl Morey, General Manager, Houston Rockets—
“Tom Davenport is the number one analytics expert in the world today. Whether you are an executive looking to integrate analytics in your decision making or a manager seeking to generate better conversations with the quants in your organization, this is the book for you.”

Jim Goodnight, cofounder and CEO, SAS—
“Analytics experts understand that the path to knowledge includes advanced data analysis. To bring everyone else up to speed, this book is required reading.”

Dr. Seung-Han Lee CBE, Chairman and CEO, Homeplus Group (Tesco Korea)—
“Insight comes from analytics. You can learn how to find treasure in your data from this book.”

Tim Phillipps, Deloitte Touche Tohmatsu Limited Global Leader, Deloitte Analytics—
“Analytics is not just a fad—it’s the future. If you are looking for a competitive data edge, this book is for you.”

Dr. Gary W. Loveman, Chairman and CEO, Caesars Entertainment, Inc.—
Keeping Up with the Quants provides a compelling and accessible road map for managers to understand the process by which analytic questions are framed, examined, and turned into powerful business insights.”


Why Everyone Needs Analytical Skills

Welcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data.

As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your “quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value.

In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including:

• How to formulate a hypothesis
• How to gather and analyze relevant data
• How to interpret and communicate analytical results
• How to develop habits of quantitative thinking
• How to deal effectively with the “quants” in your organization

Big data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.


  • Format: Kindle Edition
  • Dateigröße: 1375 KB
  • Seitenzahl der Print-Ausgabe: 241 Seiten
  • ISBN-Quelle für Seitenzahl: 142218725X
  • Verlag: Harvard Business Review Press (21. Mai 2013)
  • Verkauf durch: Amazon Media EU S.à r.l.
  • Sprache: Englisch
  • ASIN: B00B0SA1LY
  • Text-to-Speech (Vorlesemodus): Aktiviert
  • X-Ray:
  • Word Wise: Aktiviert
  • Verbesserter Schriftsatz: Nicht aktiviert
  • Durchschnittliche Kundenbewertung: Schreiben Sie die erste Bewertung
  • Amazon Bestseller-Rang: #148.631 Bezahlt in Kindle-Shop (Siehe Top 100 Bezahlt in Kindle-Shop)

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Die hilfreichsten Kundenrezensionen auf (beta) HASH(0xa537f2e8) von 5 Sternen 30 Rezensionen
22 von 23 Kunden fanden die folgende Rezension hilfreich
HASH(0xa53370fc) von 5 Sternen For Playing Well with Quants and Their Data 13. Juni 2013
Von Mark Graham - Veröffentlicht auf
Format: Gebundene Ausgabe
With data analysis becoming more important in every kind of business and organization (highlighted by Netflix, Amazon, Moneyball, and Nate Silver's political blog 538 among many others), this book offers timely advice. Keeping Up with the Quants explains the basic groundwork of the types and workings of data analysis. However, you need not be a quant to understand this book. In fact it is geared to non-quants who want to better understand how to work with the number crunchers/analysts. Even if you don't actively do the statistics yourself, it is still helpful to get up to speed on how to think about the bigger picture for using analytics.

Other books likely to be helpful include Nate Silver's bestseller The Signal and the Noise: Why So Many Predictions Fail -- but Some Don'twhich makes statistical thinking fun to read about. A Lessor known work (which I learned about it in Silver's book) is Paul E. Meehl's classic Clinical Versus Statistical Prediction. This book is definitely more technical than Silver's but is geared to working with softer, psychological/behavioral issues (for reviews of the out of print edition go here: Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence, for a lessor expensive edition here: Clinical Versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence(at this writing only the out of print edition has reviews, but it can be pricey).
23 von 25 Kunden fanden die folgende Rezension hilfreich
HASH(0xa5238348) von 5 Sternen Interesting but perhaps oversimplified 11. August 2013
Von Lauren Hirs - Veröffentlicht auf
Format: Gebundene Ausgabe
Keeping Up With the Quants was interesting enough to keep me (a 9-year veteran of a predictive analytics field) reading to the end, but I frequently felt like the book was oversimplified - even for "non-quants." If there are professionals out there who don't know some of these basics, I'm scared for the future of business. If you already know different chart types, statistical basis like R-squared and regressions, and that correlation does not equal causation, you may want to skip. That said, it's a quick enough read that it's worth a look for the gems hidden within it.

I'd judge this an ideal book for a student or new grad looking to understand basic concepts of analytics, but maybe not for experienced workers.
13 von 13 Kunden fanden die folgende Rezension hilfreich
HASH(0xa533621c) von 5 Sternen What non-quants need to understand in order to take full advantage of the results that quantitative analysis can produce 18. Juni 2013
Von Robert Morris - Veröffentlicht auf
Format: Gebundene Ausgabe
Almost everything most business leaders know about analytics they have learned from Tom Davenport and the material he provides in his books, notably in Competing in Analytics and Analytics at Work. In a more recent book, Judgment Calls, he and co-author Brooke Manville offer "an antidote for the Great Man theory of decision making and organizational performance": organizational judgment . That is, "the collective capacity to make good calls and wise moves when the need for them exceeds the scope of any single leader's direct control." The more non-quants there are in a given organization, the better prepared that organization will be to take full advantage of the results that quantitative analysis can produce, hence the importance of Judgment Calls.

Davenport wrote Keeping Up with the Quants in collaboration with Jinho Kim to demonstrate how quantitative analysis works -- even if (especially if) their reader does not have a quantitative analysis background -- and how to make better decisions. "Analytics can be classified as descriptive, predictive, or prescriptive according to the given methods, [applications,] and purpose." They examine three analytical thinking stages and how to apply them and then shift their attention to six steps of quantitative analysis. I commend them on their skillful use of various reader-friendly devices that include boxed mini-commentaries (e.g. "The Danger of NOT Thinking Analytically," Pages 19-21), Worksheets, Tables (e.g. 5-1, "Data-mining software for finding patterns in data," Page 140), Figures (e.g. 6.1, "The process of becoming a proficient quantitative analyst," Page 156), a "Summary" at the conclusion of Chapters 1-13, and real-world examples of what can be learned (i.e. do's and don'ts) from various and diverse companies and their experiences with quantitative analysis. These devices will facilitate, indeed expedite frequent review of key material later.

These are among the dozens of passages of special interest and value to me, also listed to indicate the scope of Davenport and Kim's coverage.

o What Are Analytics? (Pages 3-5)
o What Do We Mean by Big Data? (6-7)
o Ways to Measure Variables (65)
o Key Statistical Concepts and Techniques (82-86)
o Telling a Story with Data, and, What Not to Communicate (98-101)
o Purposes and Types of Visual Analytics (107-108)
o The Four Stages of Analytical Thinking (132)
o Patterns in the Leading Digit -- a Way to Detect Fraud (145-147)
o Quantitative Attitude (156-166)
o Quantitative Habits (166-175)
o Your Analytical Responsibilities (192-198)
o What Business Decision Makers Should Expect of Quantitative Analysts (200-201)

Here are Tom Davenport and Jinho Kim's final thoughts: "First, analytical thinking and decisions based on data and analytics will plan an increasingly important role in business and society...Second, we hope you now realize that you can play in this game even if you are not a statistics or math whiz...Third, while most people typically think of 'solving the problem' as the core of analytical thinking, it's only one of the steps that make for a successful analytical decision...Fourth and finally, many people believe that the world of analytical thinking and decisions is almost exclusively about numbers, rigorous statistics, and left-brain thinking in general. But the right brain needs to be seriously engaged as well."

And don't forget to buckle your seat belt.
15 von 18 Kunden fanden die folgende Rezension hilfreich
HASH(0xa52d2e58) von 5 Sternen Awesome Text for Aspiring Data Scientists AND Users... 10. Juni 2013
Von Let's Compare Options Preptorial - Veröffentlicht auf
Format: Gebundene Ausgabe
If you read the literature about new grads unable to find jobs except at McD's, one exception is a new category of job and profession called "Data Scientist" which started being used as late as 2009/2010. There now even is a CDSO--Chief Data Science Officer-- in some data intensive firms! IF your team doesn't yet have a CDSO, tell them to create the position and give it to you, especially if you're reading this review and considering purchasing this book. Entry data science: $90K range; Manager: $165K; CDSO: $220K including options, etc. (Source: DS assn.).

This little gem won't turn you into a data wonk overnight, but it IS a "condensed" Data/ MBA course (especially quantitative analysis in IT) showing the most current aspects of analysis from a big data vantage point. To be brutally honest, folks who got their MBAs even as recently as four years ago, and studied linear programming etc., are now having to once again reinvent themselves with the much more heavily statistical nature of mining, machine learning, Web X.o, etc.

My premise is: to be successful, we ALL need to be data scientists today, whether or not it fits our current job description! If you see any truth in that at all, this book is a must read. It avoids the deep math and algorithms behind the analysis, but gives very clear analogies, examples, and techniques in English to help with the most important steps: interpretation, relevance and use.

A recent trend in big data is "ala carte" dashboards, where users configure Sharepoint and other tools via Excel etc. LOCALLY. If you're not a quant, you ARE a quant CUSTOMER, and deserve to maximize the tools you have in front of you. Asking the right questions is 75% of getting that benefit. This book covers an excellent level of both overview and detail-- a nice and readable balance of why, when and how. It fits very sweetly in the vacant spot between Excel data manuals and 30,000 foot strategic tomes on the value of big data systems that frankly aren't really helpful unless you're a CTO.

3 bears again: the former can be TOO detailed, the latter not detailed enough, and this book just right-- Davenport figured out just the right missing balance between the power user, the user wannabe and us-- the practical users! Highly recommended. Oh, and if you DO want to get into this field, this text is a must have for a different reason--to see the balanced perspective of trenches users who need just the RELEVANT details in the midst of a very busy day.

Special tip: if you TEACH business or quant, you'd be doing your students a really big favor by incorporating many of this fine text's associations in your courses, as you'd be preparing them for many more of the real applications and issues they will see, with the practical knowledge of how they work and what they are and aren't suited for. Enough is covered to organize further reading and study for specialization and more depth in, say, the math, Excel, algorithms, systems, mining, software, etc.

Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.
11 von 14 Kunden fanden die folgende Rezension hilfreich
HASH(0xa528e3cc) von 5 Sternen Unless you are just starting out with stats, data, or analytics, skip this book 14. Juli 2013
Von Scott Solomon - Veröffentlicht auf
Format: Gebundene Ausgabe Verifizierter Kauf
I am a Davenport fan. Competing on Analytics and Analytics at Work (his prior analytics books), truly changed my career. For that reason, I was very excited about this book. Unfortunately, it is too basic to be helpful to anyone who read and practices the analytical mindset presented in his earlier works.
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