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

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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 informati 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.


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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 informati 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.

30 review for Keeping Up with the Quants: Your Guide to Understanding and Using Analytics

  1. 5 out of 5

    Todd N

    This is a business-focused overview of data analytics and statistics. Downloaded to my Kindle on an impulse because the author was recommended to me from a previous book. I found it to be too business-oriented and too high-level. When things are too abstract, by which I mean not enough math to nail it to my brain, I have trouble retaining the material. If you are interested in statistics and predictive analytics in general (i.e. not how to super-turbo-charge your career and companies profits!!!) t This is a business-focused overview of data analytics and statistics. Downloaded to my Kindle on an impulse because the author was recommended to me from a previous book. I found it to be too business-oriented and too high-level. When things are too abstract, by which I mean not enough math to nail it to my brain, I have trouble retaining the material. If you are interested in statistics and predictive analytics in general (i.e. not how to super-turbo-charge your career and companies profits!!!) then read Nate Silver's The Signal And The Noise. If you are interested in an overview of the techniques of data science (i.e. data mining) with just enough math to keep it from being airy-fairy, then check out Data Science For Business published by O'Reilly, which I just started reading and which looks very promising. Although I confess I didn't finish this book I feel the audience for this book is a mid-level manager to VP who needs some context after suddenly finding themselves between the bearded weirdos in the data science department and the execs who take private elevators to their offices. There are lots of useful case studies, which is the lingua franca for these types. This is not a knock on the book because it's very upfront about being a book for non-quants.

  2. 5 out of 5

    Kaushal Mahajan

    Ok. So did not learn much from this book that i already did not know before. Its quite useful however, from the perspective of the audience that this book is written for - i.e. folks who do not readily understand quantitative and statistical methods. It tries to teach middle and senior level managers how to make use of the quants on their team, or how to have a good conversation with the quants. I felt that the book is somewhat weak in advising leaders about in what situations would they need to Ok. So did not learn much from this book that i already did not know before. Its quite useful however, from the perspective of the audience that this book is written for - i.e. folks who do not readily understand quantitative and statistical methods. It tries to teach middle and senior level managers how to make use of the quants on their team, or how to have a good conversation with the quants. I felt that the book is somewhat weak in advising leaders about in what situations would they need to employ a quant. It tries to do it, but somewhat sketchily.

  3. 5 out of 5

    Dorum

    This was an ok introduction to data analysis. I think the formal description of the flow is its selling point. I disliked the fact that quite a few important concepts are presented somewhere in the middle of the book as a type of "glossary". I also would have expected something a little bit more technical. However, the careful description of the entire flow of data analysis is for me a selling point. This was an ok introduction to data analysis. I think the formal description of the flow is its selling point. I disliked the fact that quite a few important concepts are presented somewhere in the middle of the book as a type of "glossary". I also would have expected something a little bit more technical. However, the careful description of the entire flow of data analysis is for me a selling point.

  4. 4 out of 5

    Ken

    This is a very good book that is easy to read and gives the reader a good idea on how to do some "analytics". Industries are changing and data is so prevalent and abundant that people need to be aware what is happening and what they can/should be doing. A lot has been said about an innumerate population, but we could be heading towards a quantitative illiterate population too. The book is broken into two sections - the explanation of the the analytical skills and then examples of how they are app This is a very good book that is easy to read and gives the reader a good idea on how to do some "analytics". Industries are changing and data is so prevalent and abundant that people need to be aware what is happening and what they can/should be doing. A lot has been said about an innumerate population, but we could be heading towards a quantitative illiterate population too. The book is broken into two sections - the explanation of the the analytical skills and then examples of how they are applied.

  5. 5 out of 5

    Zaher Alhaj

    This book might be useful one for a completely novice reader on the subject. I found it pretty shallow and repetitive. If you want to get your hand onto a good introductory framework about "Data" in business context, then I would ,instead, highly recommend "Data Fluency: Empowering Your Organization with Effective Data Communication". This book might be useful one for a completely novice reader on the subject. I found it pretty shallow and repetitive. If you want to get your hand onto a good introductory framework about "Data" in business context, then I would ,instead, highly recommend "Data Fluency: Empowering Your Organization with Effective Data Communication".

  6. 5 out of 5

    Rudranil Ghosh

    This book is more like an easy read for people to get acquainted to the business analytics field ...the examples in the book do throw some interesting insights about the analytical approaches companies are taking in today's world. This book is more like an easy read for people to get acquainted to the business analytics field ...the examples in the book do throw some interesting insights about the analytical approaches companies are taking in today's world.

  7. 4 out of 5

    Ariadna73

    This book tries to describe 4 stages of analytical thinking, but in the end, there is nothing new in it. I think anyone interested in the topic could do without this one just fine.

  8. 4 out of 5

    BLACK CAT

    Detailed. Tools, techniques, people, trends, analytical masters, inspiring insightful stories... It is too detailed for an audio book but might be better in printed format.

  9. 5 out of 5

    Bruce Bahlmann

    Only marginally useful

  10. 4 out of 5

    Marcin Nowak

    quite down-to-the-ground manual for non-technical people on how to deal with data engineers. sometimes a bit boring, but I might be biased.

  11. 5 out of 5

    Sean Zhang

    I didn't like this book very much but it has been pretty informative. I didn't like this book very much but it has been pretty informative.

  12. 5 out of 5

    Phillias

    Intro. Not rigorous. More of an advertisement for data scientists. Proof that they want everyone else to bend to their will. Ex titles "Working with quants" "won't make you feel stupid" lol. Intro. Not rigorous. More of an advertisement for data scientists. Proof that they want everyone else to bend to their will. Ex titles "Working with quants" "won't make you feel stupid" lol.

  13. 4 out of 5

    Fred Cheyunski

    Understanding/Learning to Utilize New Data/Analytic Capabilities - This book offers a useful means for keeping up with the burgeoning field of analytics. As Davenport and Kim state “the world is awash with data” and their aim is to explain how quantitative analysis works and how to use such analyses to make decisions in our increasingly quantified and monetized environment. Within the book, the authors convey a simple three stage, six step quantitative analysis approach or framework. More specifi Understanding/Learning to Utilize New Data/Analytic Capabilities - This book offers a useful means for keeping up with the burgeoning field of analytics. As Davenport and Kim state “the world is awash with data” and their aim is to explain how quantitative analysis works and how to use such analyses to make decisions in our increasingly quantified and monetized environment. Within the book, the authors convey a simple three stage, six step quantitative analysis approach or framework. More specifically, their approach consists of I) Framing the Problem via (1) Problem Recognition and (2) Review of Previous Findings, II) Solving the Problem with (3) Modeling, (4) Data Collection, and (5) Data Analysis, then III) Communicating and Acting on Results through (6) Results Presentation and Action. (They also integrate four stages of creative analytic thinking with their core method.) Davenport and Kim proceed by explaining all six steps and ways they are employed. They utilize many charts, diagrams, illustrations and side bars. For instance, in a pictorial manner, they have lists such as “What Kinds of Decisions Can Be Made Using Analytics” and “Good Questions About Quantitative Analyses” There are also “Worksheets” and “call outs” at various points in the book like the ones for “Framing the Problem” and “What Decision Makers Can Expect from Quantitative Analysts.” Among sections that were most interesting to me were the ones on “Identifying [and Involving] Stakeholders,” “Modeling,” and “Telling a Story with Data.” Stakeholders can help determine important data elements and the form reporting should take. Modeling as a simplified representation of the phenomenon or problem can help focus on the most important aspects. Visual analytics (or use of software for data visualization) can be powerful in dynamically presenting information to support decision making. The book is Davenport’s third on analytics building on his previous works (with others as well) about companies whose strategies are based on analytics (“Competing on Analytics”) as well as ways analytics have been incorporated in the workings of various organizations (“Analytics at Work”). All three are valuable in presenting the importance and ways of dealing with data. However, this one is particularly helpful to those of us who are managers and users in better understanding and learning ways to utilize these important new capabilities.

  14. 5 out of 5

    Andy Scott

    I read this book for one of my grad classes. It was a good read. Easy to follow, nicely organized, practical advice, and lots of interesting example cases. I appreciated the actionable suggestions towards the end of the book. It made me think seriously about identifying the problems in my work of teaching and seeking quantitative solutions to them, figuring out what data to collect in order to draw a valid conclusion/solution. It would also be interesting to consider having a school district hir I read this book for one of my grad classes. It was a good read. Easy to follow, nicely organized, practical advice, and lots of interesting example cases. I appreciated the actionable suggestions towards the end of the book. It made me think seriously about identifying the problems in my work of teaching and seeking quantitative solutions to them, figuring out what data to collect in order to draw a valid conclusion/solution. It would also be interesting to consider having a school district hire a data analyst to help with finding solutions to educational challenges, and even help with hiring and firing of teachers, Moneyball style. Obviously, there is a lot of previous educational research to sift through, but developing the analytical habits and skills that lead to legitimate solutions for me personally might bring greater success and value to my teaching. One of the most interesting examples was a study about two researchers, James Murray and John Gottman, who developed a model to predict whether couples' marriages would end in divorce. They found success by analyzing couples' conversations about a contentious issue, looking for certain expressions such as humor, joy, agreement, affection, anger, defensiveness, disgust, and contempt. From their research, Gottman and his wife have developed materials to help couples overcome destructive communication patterns (www.gottman.com).

  15. 4 out of 5

    Steven

    This book contains good insights for aspiring business leaders with interest in becoming more analytical (which should be every business leader to be honest.) This is not a book about complex mathematical predictive models (those are for the quants) or quantitative methods. This is for business leaders to work with quants (mathematically oriented individuals) and collaborate on solving complex business problems. This is not to say understanding those “complex mathematical models” is not importan This book contains good insights for aspiring business leaders with interest in becoming more analytical (which should be every business leader to be honest.) This is not a book about complex mathematical predictive models (those are for the quants) or quantitative methods. This is for business leaders to work with quants (mathematically oriented individuals) and collaborate on solving complex business problems. This is not to say understanding those “complex mathematical models” is not important, but this book serves as a good starting point to develop the analytical mindset we all need to have. Great book highly recommended!

  16. 5 out of 5

    Rafael

    I really enjoyed this book. It was well written with a healthy amount of charts to explain and summarize ideas. This book explains the background and process to use analytics without dumbing things down or over generalizing. The point of the book is to explain what is needed to understand and work with analytics, and I found it very helpful. If I choose to pursue a deeper understanding of analytic problem solving, this book will be the reason for that. I definitely plan to revisit this book for I really enjoyed this book. It was well written with a healthy amount of charts to explain and summarize ideas. This book explains the background and process to use analytics without dumbing things down or over generalizing. The point of the book is to explain what is needed to understand and work with analytics, and I found it very helpful. If I choose to pursue a deeper understanding of analytic problem solving, this book will be the reason for that. I definitely plan to revisit this book for future use.

  17. 5 out of 5

    Jair Benavidez

    This is a book for people with very little or no understanding of statistics and especially how this field can help business people make better decisions based on data. It gives a framework so non-quants can follow and understand the process and the general thinking behind. The book also give more resources to keep the business people learning and being more data driven. Something is not for the future but that so many companies need urgently today.

  18. 4 out of 5

    Jeff Huang

    A fun read, but it does not provide enough insight into how to create models, how to identify variables, and how to analyze data. To be fair the book states that it is not for aspiring quants, but for people keeping up with them. However not everyone has to be a professional quant to want to develop the quant habits advocated for in the book.

  19. 5 out of 5

    Ali

    It's a beautiful and nice book for all the people with absolutely no background in Data Sciences. This book has been designed for all this decision makers in business and government sector who really wants to take benefit of Big Data. Another good thing is that the book is full of examples where data has been intelligently utilized to infer important scientific and managerial decisions. It's a beautiful and nice book for all the people with absolutely no background in Data Sciences. This book has been designed for all this decision makers in business and government sector who really wants to take benefit of Big Data. Another good thing is that the book is full of examples where data has been intelligently utilized to infer important scientific and managerial decisions.

  20. 5 out of 5

    CBru1011

    This book was suggested by the Certified Analyst Professional test exam study guide. It's a nice general book for people interested in the analysis process. It reads at a nice pase, and its not overly detailed or technical. Its a little old with an original copy write date of 2013, but it's updated and relevant, today. This book was suggested by the Certified Analyst Professional test exam study guide. It's a nice general book for people interested in the analysis process. It reads at a nice pase, and its not overly detailed or technical. Its a little old with an original copy write date of 2013, but it's updated and relevant, today.

  21. 5 out of 5

    Ravi

    In very simple language, author take us to a journey of process of problem solving while stopping at each step and explain them. Midway briefly introducing concepts of big data and quantitative analysis remaining slightly statistics oriented.

  22. 5 out of 5

    Rodrigo Leão

    The best book I´ve read about analytics!

  23. 4 out of 5

    Meghan

    Really good application of quant to people and business.

  24. 5 out of 5

    Bryn

    *3.5. Pretty interesting for something I had to read for class.

  25. 4 out of 5

    Dirk

    Boring but educational

  26. 5 out of 5

    Siah

    Pure fluff. This is for someone who has zero experience in the field. Do not read.

  27. 4 out of 5

    Gavin

    Helpful for understanding usage in business.

  28. 5 out of 5

    Angela

    an interesting read. i read it as part of a group of suggested material so i'm not able to give a very precise review, as the other material and this book are combined in my mind. an interesting read. i read it as part of a group of suggested material so i'm not able to give a very precise review, as the other material and this book are combined in my mind.

  29. 5 out of 5

    Theresa Jehlik

    Davenport and Kim have written a readable book about analytics with sidebars into big data and statistics. They frame analytics into a three-step process -- framing the problem, solving the problem, and communicating and acting on the results. They are quick to say that many people never get to the third step which is the most important. With examples ranging from the Fido Index to determine one's suitability for a pet (Kim found that even a pet cactus would be ambitious for him) to why a 10-mon Davenport and Kim have written a readable book about analytics with sidebars into big data and statistics. They frame analytics into a three-step process -- framing the problem, solving the problem, and communicating and acting on the results. They are quick to say that many people never get to the third step which is the most important. With examples ranging from the Fido Index to determine one's suitability for a pet (Kim found that even a pet cactus would be ambitious for him) to why a 10-month pregnancy is possible to the "nun study" about linguistics and Alzheimer's Disease, the authors are entertaining with what is normally considered very dull material. A good introduction to some timely topics.

  30. 5 out of 5

    Xuejin Chuang

    Targeted at business people or non-data scientists, Keeping up with the Quants provides a good overview on how to approach data science projects without going into the mathematics details. It describes a simple methodology (nothing too novel) on how to work with data scientists and stakeholders to use data to solve problems. Worth reading if you need to quickly understand how to implement data science processes in your business. In this book it also recommends what else to read depending on your Targeted at business people or non-data scientists, Keeping up with the Quants provides a good overview on how to approach data science projects without going into the mathematics details. It describes a simple methodology (nothing too novel) on how to work with data scientists and stakeholders to use data to solve problems. Worth reading if you need to quickly understand how to implement data science processes in your business. In this book it also recommends what else to read depending on your needs. ** DON'T EXPECT TOO MUCH if you are already acquainted with data science and analytics. **

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