Data Science for Business: What you need to know about data mining and data-analytic thinking

With the growth of concepts such as big data and increasing need to experts who can conduct business analytics, knowing about nuts and bolts of data science is more important than ever.

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business: What you need to know about data mining and data-analytic thinking 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.

This book tells you how to **think** from the angle of data when you make decisions. We have read so many data mining books. They often claim themselves practical simply because they provide examples in addition to the technical details. Well, this statement can be seriously misleading since no one is going to solve the same problem as the one in the book. Without a good explanation on the intuition underlying the technique, it is hard to make true links with examples and eventually even harder, if not possible, to extend what you read to what you need to solve in real applications.

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
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