Data Science for Business: What you need to know about data mining and data-analytic thinking
- Downloads：2033
- Type：Epub+TxT+PDF+Mobi
- Create Date：2021-10-01 08:53:52
- Update Date：2025-09-06
- Status：finish
- Author：Foster Provost
- ISBN：1449361323
- Environment：PC/Android/iPhone/iPad/Kindle
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Summary
Written by renowned data science experts Foster Provost and Tom Fawcett， Data Science for Business introduces the fundamental principles of data science， and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect。 This guide also helps you understand the many data-mining techniques in use today。
Based on an MBA course Provost has taught at New York University over the past ten years， Data Science for Business provides examples of real-world business problems to illustrate these principles。 You’ll not only learn how to improve communication between business stakeholders and data scientists， but also how participate intelligently in your company’s data science projects。 You’ll also discover how to think data-analytically， and fully appreciate how data science methods can support business decision-making。
Understand how data science fits in your organization—and how you can use it for competitive advantage
Treat data as a business asset that requires careful investment if you’re to gain real value
Approach business problems data-analytically， using the data-mining process to gather good data in the most appropriate way
Learn general concepts for actually extracting knowledge from data
Apply data science principles when interviewing data science job candidates
Based on an MBA course Provost has taught at New York University over the past ten years， Data Science for Business provides examples of real-world business problems to illustrate these principles。 You’ll not only learn how to improve communication between business stakeholders and data scientists， but also how participate intelligently in your company’s data science projects。 You’ll also discover how to think data-analytically， and fully appreciate how data science methods can support business decision-making。
Understand how data science fits in your organization—and how you can use it for competitive advantage
Treat data as a business asset that requires careful investment if you’re to gain real value
Approach business problems data-analytically， using the data-mining process to gather good data in the most appropriate way
Learn general concepts for actually extracting knowledge from data
Apply data science principles when interviewing data science job candidates
Reviews
Boris
，
Good book for a junior data scientist， very comprehensive and practical。
Ufo
，
THIS BOOK IS AMAZING！！！ The knowledge in this book is super practical with clear， in-depth explanations and real-life examples， such as churn prediction model， conversion rate prediction for marketing campaigns， product purchase prediction， etc。 For each of the examples， the author shows his in-depth knowledge of both business and data。 He can walk you through the thought process of how to distill a generic business problem into a specific business-centered data problem。 He even points out the c THIS BOOK IS AMAZING！！！ The knowledge in this book is super practical with clear， in-depth explanations and real-life examples， such as churn prediction model， conversion rate prediction for marketing campaigns， product purchase prediction， etc。 For each of the examples， the author shows his in-depth knowledge of both business and data。 He can walk you through the thought process of how to distill a generic business problem into a specific business-centered data problem。 He even points out the common mistakes and pitfalls so you can avoid。I'm not a data scientist myself。 I am a Product Manage that loves data and loves working with data to solve real problems。 I really appreciate seeing how he analyzes and solves a problem from both business and data points of view。 The book really lived up to its title。 The author clearly explains to you the fundamental concepts of each technique and formula so that you won't just apply it blindly but you can apply it with confidence understanding the why behind it。 This book gave me so many Aha！ moments - "Oh， I see！ That's why！" kind of moment。 If you're not a data scientist like me， this book is still super helpful if you are working or going to work with data scientists。 You will understand their world and thinking much better。 I cannot recommend this book enough！！！！ 。。。more
𝛑Cutie
，
Có thể xem là một quyển textbook tốt về Data Science。 Phần nội dung mang tính giới thiệu chiếm cỡ 30%， còn lại là những kiến thức mà tác giả cho là nền tảng trong ngành。 Sách viết cô động， giải thích dễ hiểu， có link nhiều articles/papers để đọc thêm; phù hợp với những ai đang bắt đầu tìm hiểu lĩnh vực này。
Tim Yang
，
A challenging yet informative read for those who don’t have a data science background。 The book focuses on teaching you fundamental principles and applications of those principles in the form of techniques such as classification trees， logistic regressions， expected value analysis， ROC/AUC， lift/leverage and more。 At times the book read a bit like a textbook in the sense that the information was quite dense， but that also meant you’ll learn a lot in the span of just about 350 pages。 I highly rec A challenging yet informative read for those who don’t have a data science background。 The book focuses on teaching you fundamental principles and applications of those principles in the form of techniques such as classification trees， logistic regressions， expected value analysis， ROC/AUC， lift/leverage and more。 At times the book read a bit like a textbook in the sense that the information was quite dense， but that also meant you’ll learn a lot in the span of just about 350 pages。 I highly recommend a read if you’re a business student who took only one statistics class， and want to know more on how these data science could be useful for businesses。 。。。more
Ramasubramaniam
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A good intro to data science with a non technical presentation。
Alok Pepakayala
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This book is pretty aptly titled and written with a specific purpose to explain several ideas to a very specific target audience， not just for the sake of it or because they can sell it， but its very much necessary to fill a void that actually exists。 Its also written by people with good hands-on experience on the topic who expressed their knowledge in a very intuitive way that the reader follows pretty easily， but at the same time its just a book for business people and reading it doesn't make This book is pretty aptly titled and written with a specific purpose to explain several ideas to a very specific target audience， not just for the sake of it or because they can sell it， but its very much necessary to fill a void that actually exists。 Its also written by people with good hands-on experience on the topic who expressed their knowledge in a very intuitive way that the reader follows pretty easily， but at the same time its just a book for business people and reading it doesn't make one any way qualified to handle such decisions。 Its like reading about how to work with detectives， doesn't make you one。 I can really recommend this to many people for various reasons， mostly to people in data science to help share their ideas to the business audience。 。。。more
Surbhi Jain
，
I would like to thank you for the efforts you have made in writing this article。 I am hoping the same best work from you in the future as well。 In fact your creative writing abilities has inspired me to start my own Blog Engine blog now。 Really the blogging is spreading its wings rapidly。 Your article is a fine example of it。Data science classes in puneData science Course in puneData science Training in pune I would like to thank you for the efforts you have made in writing this article。 I am hoping the same best work from you in the future as well。 In fact your creative writing abilities has inspired me to start my own Blog Engine blog now。 Really the blogging is spreading its wings rapidly。 Your article is a fine example of it。Data science classes in puneData science Course in puneData science Training in pune 。。。more
Jonas Toftefors
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A clear introduction to different machine learning technologies as well as tooling for evaluating the results。
K Nijs
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The book learns thinking about problems in a data analytically way。 It's discussing the various statistical and machine learning methods， as also the way you're looking at the problem and the desired solution yourself。I like the reasoning of the Expected Value Framework and the （Business Case） Starting Review Guide （Appendix A）。 Taking the baseline into account when evaluating the model， using cross-validation， 。。。The writers clearly have practical experience in the field， but that doesn't make The book learns thinking about problems in a data analytically way。 It's discussing the various statistical and machine learning methods， as also the way you're looking at the problem and the desired solution yourself。I like the reasoning of the Expected Value Framework and the （Business Case） Starting Review Guide （Appendix A）。 Taking the baseline into account when evaluating the model， using cross-validation， 。。。The writers clearly have practical experience in the field， but that doesn't make the book easy to read。It's rather difficulty written:- Very verbose: it should have used lists， workflows， images， visualizations， 。。。- Repetitive examples and references back and forth。 Eg。 reading chapter 12: "keep in mind 。。。 introduced in Chapter 4 and elaborated in Chapter 7"。- With the use of elaborate， detailed descriptions of each step of the analysis， the text becomes hard to read。Eg。 there's a page-long conclusion written about not having data， and to just give it a try to learn from practice。 This could be one paragraph。- For some reason， there's also a constant condescending tone towards Data Analysts- Reuse of the same examples （as in all AI literature）: churn and next best offer。The book ends with a general management advice in business speak: "managers need to do this"， "culture has to be like that"， 。。。 I think the "jack of all trades 。。。" quote is applicable here。To get a head start in Data Science （for Business）， I would advise:- Coursera- The book 'Machine learning for everyone' by 'vas3k'- The book 'Machine learning for humans'To end with a quote from this book that describes my feeling: "It is possible to keep elaborating the business problem into greater and greater detail， uncovering additional complexity in the problem。 You may wonder: Where does this all end？ Can’t I keep pushing the analysis on forever？" 。。。more
kurp
，
Dobra książka， podchodząca do tematu od strony biznesowej użyteczności， za co autorom chwała。 Czytałem w tłumaczeniu， dzięki czemu odkryłem nieco polskich odpowiedników anglojęzycznych pojęć （nawiasem， przydałoby się uwzględnienie w treści także tych oryginalnych） i teraz będę mniej kaleczył mowę ojczystą ;）
Kuba
，
4-4。5， ale polskie tłumaczenie było straszne。 Nie polecam。
Shelly （YI-Hsuan） LIN
，
A great book to understand the data science from business perspectives。 I really enjoy the way author explains data science concept。 Definitely a worth reading book for people with business background who wants to gain knowledge about data science！
Đạt
，
For a beginner without Maths background， this book is really challenging。Even thou i can't digest all the lessons and ideas in this book， it still gives me tons of motivation to go back and learn maths which hopefully help me understand this book more。It's really a good book For a beginner without Maths background， this book is really challenging。Even thou i can't digest all the lessons and ideas in this book， it still gives me tons of motivation to go back and learn maths which hopefully help me understand this book more。It's really a good book 。。。more
B。 Mulenga Sindala
，
Data Science without most of the mathematics。
Jorge Pablo
，
Worth reading， im studying data science and this book gave me ideas on how to apply models on bussiness。
GColucci
，
not an easy read， but a great intro to the world if data science。 Read it as part of the KUL postgraduate programme in big data and analytics。
John Tyler
，
Essential reading for any analytics manager。
Rohan Purohit
，
I am currently reading this book for college， its well organized， easy to understand and practical。 This book is a good overview of analyzing data for statistical fundamentals of measures of central tendency， variance， bias， error。 It also goes over how to follow the iterative cycle of the CRISP DM methodology to develop a data science project starting from business understanding， data understanding， data preparation， modeling， evaluation to deployment and maintanence。 The authors illustrate sev I am currently reading this book for college， its well organized， easy to understand and practical。 This book is a good overview of analyzing data for statistical fundamentals of measures of central tendency， variance， bias， error。 It also goes over how to follow the iterative cycle of the CRISP DM methodology to develop a data science project starting from business understanding， data understanding， data preparation， modeling， evaluation to deployment and maintanence。 The authors illustrate several concepts important to data science such as partitioning data， selecting algorithms for classification， clustering and simulation for supervised and unsupervised data science problems。Several pitfalls are discussed in evaluating data science projects and proposals especially in Apendix A and B。 Algorithm bias is hinted at by a discussion of ROC Curves， AUC metrics， Penalty functions for misclassifications。 Confusion matrices are also discussed brining up specificity and sensitivity of the data set along with precision， accuracy and recall。 Text mining is also discussed in a chapter dedicated to concepts such as IDF， Document Term Matrices etc。 Overall its a good book to get started in data science。 。。。more
Anjar Priandoyo
，
Actually a good book for Data Science， however， I am looking for more general book on Data Management。 I will skip as of now。 Will reread again one day。
Tobias
，
Excellent for the basis of data science
Toni Tassani
，
I was expecting a quick read to understand better Data Science， but it is a text book。 You get a good idea of usages and strategies， with only some maths。 I liked the references to teams， hiring and the market， but they were shallow。 It was hard to read。
Vitor Hirota
，
O livro fornece várias aplicações da ciência de dados no ambiente de negócios， com boas práticas， cuidados e métricas de avaliação。 Uma boa introdução para aspirantes a cientista， talvez uma boa revisão sobre como gerar valor para quem já prática， e também uma boa leitura para gerentes que queiram ter melhor idéia sobre o assunto e evitar que sejam acuados por jargões e "cortinas de fumaça" durante uma discussão com cientistas。 A avaliação é feita com base na versão traduzida， e em minha própria O livro fornece várias aplicações da ciência de dados no ambiente de negócios， com boas práticas， cuidados e métricas de avaliação。 Uma boa introdução para aspirantes a cientista， talvez uma boa revisão sobre como gerar valor para quem já prática， e também uma boa leitura para gerentes que queiram ter melhor idéia sobre o assunto e evitar que sejam acuados por jargões e "cortinas de fumaça" durante uma discussão com cientistas。 A avaliação é feita com base na versão traduzida， e em minha própria percepção， obviamente。 Mas， por conta do conteúdo técnico， por vezes causou confusão ao utilizar termos que não necessariamente são os comumente usados na prática， como agrupamento vs segmentação para clustering; ou expressões traduzidas no texto， e em fórmulas não。 Portanto， se possível， escolha a versão original。 。。。more
Raul Tornel
，
Great intro to Datascience topics
Radek Cimr
，
Incredibly verbose but overall good content。 Could probably use a bit of a trim。
Andrii Tymchuk
，
The first two chapters had given me a bad expectation from the rest of the book with all those exclamations like "we'll discuss this， and this， but very-very shortly， and without math"。 But it was an enjoyable journey throughout the basic Data Science milestones， or， as it's called in the book， fundamental concepts。I've had some experience with statistics only during my university degree， so I can't call myself advanced expert in the field of this book。 That's the reason the level if math in the The first two chapters had given me a bad expectation from the rest of the book with all those exclamations like "we'll discuss this， and this， but very-very shortly， and without math"。 But it was an enjoyable journey throughout the basic Data Science milestones， or， as it's called in the book， fundamental concepts。I've had some experience with statistics only during my university degree， so I can't call myself advanced expert in the field of this book。 That's the reason the level if math in the book was totally suitable for me。 But taking into account the fact that the main audience of the book is managers who already face with professional challenges， the math simplification principle， which was applied to the content of this book， was a bit confusing to me。I was completely satisfied with the knowledge I've got from this book， but I've been left with only one question: do American business practitioners scare of math so much？🤔 。。。more
Luciano Lisiotti
，
Clear book to understand the basics of Data Science。Sometimes it gets complicated， but any Data Scientist can provide better angles to get the concept easily
Anton Holmström
，
Superb introduction to data mining and it's usage in business。 This book does not focus on the technical side， but rather on high level description and explanation of data mining methods and it's area of use。 Would recommend to people whom are interested in data mining and it's business usage。 Superb introduction to data mining and it's usage in business。 This book does not focus on the technical side， but rather on high level description and explanation of data mining methods and it's area of use。 Would recommend to people whom are interested in data mining and it's business usage。 。。。more
Paul Adams
，
More technical than I was looking for。 A hard read。 Had some good tips throughout。
Ramil
，
Mövzu ilə heç tanış olmayan birinə inanılmaz sıxıcı gələcək。 Mövzu ilə az çox tanış olan birisinə bəzi yerlərdə sıxıcı olmasına baxmayaraq， başqa mənbələrə yönəlməsi üçün yaxşı fundamental biliklər qazandıracaq。
Julia
，