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Data Analysis with Open Source Tools

Data Analysis with Open Source Tools

Data Analysis with Open Source Tools Paperback - 2010

by Janert, Philipp K

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Anyone can apply data analysis tools and get results, but without the right approach those results may be useless. Janert teaches readers how to "think" about data: how to effectively approach data analysis problems, and how to extract all of the available information from data.

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O'Reilly Media, 2010-11-28. Paperback. New. 1.4000 in x 9.0000 in x 7.0000 in.
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Details

  • Title Data Analysis with Open Source Tools
  • Author Janert, Philipp K
  • Binding Paperback
  • Edition [ Edition: first
  • Condition New
  • Pages 530
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media
  • Publication date 2010-11-28
  • Illustrated Yes
  • Features Illustrated, Index, Price on Product - Canadian
  • Bookseller's Inventory # mon0000223907
  • ISBN 9780596802356 / 0596802358
  • Weight 1.85 lbs (0.84 kg)
  • Dimensions 9.2 x 7 x 1.4 in (23.37 x 17.78 x 3.56 cm)
  • Size 1.4000 in x 9.0000 in x 7.0000 i
  • Category Computers - Other Applications
  • Library of Congress subjects Open source software, Data mining - Computer programs
  • Dewey Decimal Code 005.3
  • Quantity available 2

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From the publisher

Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications.

Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you.

  • Use graphics to describe data with one, two, or dozens of variables
  • Develop conceptual models using back-of-the-envelope calculations, as well as scaling and probability arguments
  • Mine data with computationally intensive methods such as simulation and clustering
  • Make your conclusions understandable through reports, dashboards, and other metrics programs
  • Understand financial calculations, including the time-value of money
  • Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations
  • Become familiar with different open source programming environments for data analysis

"Finally, a concise reference for understanding how to conquer piles of data." --Austin King, Senior Web Developer, Mozilla

"An indispensable text for aspiring data scientists." --Michael E. Driscoll, CEO/Founder, Dataspora

Media reviews

Citations

  • Reference and Research Bk News, 02/01/2011, Page 247

About the author

After previous careers in physics and softwaredevelopment, Philipp K. Janert currentlyprovides consulting services for data analysis, algorithm development, and mathematical modeling.He has worked for small start-ups and in largecorporate environments, both in the U.S. andoverseas. He prefers simple solutions that workto complicated ones that don't, and thinks thatpurpose is more important than process. Philippis the author of Gnuplot in Action - UnderstandingData with Graphs (Manning Publications), and haswritten for the O'Reilly Network, IBM developerWorks, and IEEE Software. He is named inventor on a handfulof patents, and is an occasional contributor to CPAN.He holds a Ph.D. in theoretical physics from theUniversity of Washington. Visit his company websiteat www.principal-value.com.

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