Data Science for BusinessData Science for Business
[What You Need to Know About Data Mining and Data-analytic Thinking]
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Book, 2013
Current format, Book, 2013, 1st ed, Available .This plain language text/reference explains basics of data science, data mining, and data analysis for those in business who will be working with data scientists, managing data science-oriented projects, or investing in data science ventures; developers who will be implementing data science solutions; and aspiring data scientists. The book can also be used as a textbook for a variety of data science courses at the MBA level. The book does not assume a sophisticated math background and avoids an algorithm-centered approach; instead, it explores concepts that underlie the analysis of data-centered business problems, the creation and evaluation of data science solutions, and the evaluation of general data science strategies and proposals. The book's visual approach describes procedural details with a combination of text and b&w charts, graphs, process diagrams, and visual metaphors. Appendices offer sample proposals and a glossary. A companion web site offers instructor resources. Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com)
Introduces fundamental concepts of data science necessary for extracting useful information from data mining techniques, including envisioning the problem, applying data science techniques, and deploying results to improve decision making.
<div><p>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.</p><p>Based on an MBA course Provost has taught at New York University over the past ten years, <i>Data Science for Business</i> 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.</p><ul><li>Understand how data science fits in your organization—and how you can use it for competitive advantage</li><li>Treat data as a business asset that requires careful investment if you’re to gain real value</li><li>Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way</li><li>Learn general concepts for actually extracting knowledge from data</li><li>Apply data science principles when interviewing data science job candidates</li></ul></div>
Introduces fundamental concepts of data science necessary for extracting useful information from data mining techniques, including envisioning the problem, applying data science techniques, and deploying results to improve decision making.
<div><p>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.</p><p>Based on an MBA course Provost has taught at New York University over the past ten years, <i>Data Science for Business</i> 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.</p><ul><li>Understand how data science fits in your organization—and how you can use it for competitive advantage</li><li>Treat data as a business asset that requires careful investment if you’re to gain real value</li><li>Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way</li><li>Learn general concepts for actually extracting knowledge from data</li><li>Apply data science principles when interviewing data science job candidates</li></ul></div>
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- Sebastopol, CA : O'Reilly, 2013.
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