Data Analysis with Open Source Tools

Collectingdata is relatively easy, but turning raw information into something usefulrequires that you know how to extract precisely what you need. With thisinsightful book, intermediate to experienced programmers interested in dataanalysis 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 capturethose ideas in conceptual models, and then feed your understanding back intothe organization through business plans, metrics dashboards, and otherapplications.

Alongthe way, you'll experiment with concepts through hands-on workshops at the endof each chapter. Above all, you'll learn how to think about the results youwant 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