Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

ISBN-13: 9781449361327

ISBN-10: 1449361323

Author: Foster Provost, Tom Fawcett

Edition: 1

Publication date:
2013
Publisher:
O'Reilly Media
Format:
Paperback 414 pages
Category:
Business, Engineering, Database
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Summary

Acknowledged author Foster Provost wrote Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking comprising 414 pages back in 2013. Textbook and etextbook are published under ISBN 1449361323 and 9781449361327. Since then Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking textbook received total rating of 4 stars and was available to sell back to BooksRun online for the top buyback price of $11.33 or rent at the marketplace.


Description

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 advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates