W. Edwards Deming: "The most important things cannot be measured... The most important things are unknown or unknowable." (at General Motors Technical Center in Warren, Michigan, October, 1991)

Edwards Deming - Wikipedia, the free encyclopedia.innovator of statistical process control for optimal outcomes.

Davenport et al., Analytics at Work: Smarter Decisions, Better Results. Most companies have massive amounts of data at their disposal, yet fail to utilize it in any meaningful way. But a powerful new business tool - analytics - is enabling many firms to aggressively leverage their data in key business decisions and processes, with impressive results....

Analytics at Work: Smarter Decisions, Better Results Authors: Thomas H. Davenport, Jeanne G. Harris, and Robert Morison Publication Date: Description: This is your 'How-to' guide for putting to work and developing an analytic capability in

Explains why anything perceived to be “immeasurable”, but important, can be still measured in a practical way. Readers will learn how any problem, no matter how difficult, ill-defined, or uncertain can be solved with proven measurement methods. Numerous cases and examples ranging from quality, security, customer satisfaction, the environment, risk and many more make this text applicable to virtually any manager who has to make decisions under uncertainty.

This looks like a good read for community measurement. given all of the intangibles.

Weka 3: Data Mining Software in Java    Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Machine Learning Project at the University of Waikato in New Zealand

There is a clear growing interest in the decision processes and data mining. For example, here's a new Springer Journal (that is all open content).

Decision Analytics - a SpringerOpen journal

Revolutions. News about R, statistics, big data analytics, data science, and the world of open source from the staff of Revolution Analytics. (from Revolution Analytics, http://www.revolutionanalytics.com)

Learn about using open source R for big data analysis, predictive modeling, data science

Data is just raw information -- to make that information meaningful, it has to be organized, filtered, and analyzed. Anyone can apply data analysis tools and get results, but without the right approach those results may be useless. This book shows how to effectively approach data analysis problems, and how to extract all of the available information from your data.

Turning raw data 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.

One of the clearest, cleanest texts on data mining. While it mentions the WEKA toolkit, its descriptions and explanations of data mining algorithms are insightful for any toolkit.

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)/Ian H. Witten, Eibe Frank, Mark A.

The mission of the Software Analytics Group at Microsoft Research Asia is to advance the state of the art in the software analytics area; and utilize our technologies to help improve the quality of software and services as well as the development productivity for both Microsoft and software industry. They have a large list of publications and presentations on the topic of software analytics.

Software Analytics

The mission of the Software Analytics Group at Microsoft Research Asia is to advance the state of the art in the software analytics area; and utilize our technologies to help improve the quality of software and services as well as the development productivity for both Microsoft and software industry. They have a large list of publications and presentations on the topic of software analytics.

Moneyball for software engineering. How metrics-driven decisions can build better software teams (by Jonathan Alexander)

Don't dismiss Moneyball just because it began in the sports world. Many of the system's metrics-based techniques can also apply to software teams.

Sometimes, all you really need are a few diagrams. When data mining is overkill, why not apply simpler methods like generate plots with GNUPLOT? See the GNUPLOT book http://www.manning.com/janert/ or the advanced FAQ: http://t16web.lanl.gov/Kawano/gnuplot/index-e.html

Demo scripts for gnuplot version

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