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Title details for Data Analysis with Open Source Tools by Philipp K. Janert - Available

Data Analysis with Open Source Tools

by Philipp K. Janert
ebook
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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

    Expand title description text
    Publisher: O'Reilly Media

    Kindle Book

    • Release date: November 11, 2010

    OverDrive Read

    • ISBN: 9781449396657
    • File size: 8045 KB
    • Release date: November 11, 2010

    EPUB ebook

    • ISBN: 9781449396657
    • File size: 6982 KB
    • Release date: November 11, 2010

    Formats

    Kindle Book
    OverDrive Read
    EPUB ebook

    subjects

    Computer Technology Nonfiction

    Languages

    English

    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

    Expand title description text
    Computer Technology Nonfiction