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Perl + R: Open Source Programs Simplify Data Manipulation

Extracting data from huge data stores for real-time reporting and analysis can be frustrating, especially if your data processes rely on bulky, expensive apps designed for a large-scale enterprise. Perl and R are two open source technologies that can be used to simplify everyday data extraction needs, cheaply and easily.  


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hanks to the driving technologies of the 90s—namely, the Internet and enterprise databases—data collection and storage have become easier and cheaper than ever before. This has caused many organizations to shift their focus to data extraction and analysis components. In this new era, "traditional" tabular reporting packages now seem lacking. Expectations like real-time information are hard to live up to—especially for many smaller organizations. Developments at the data extraction layer are lagging—despite the fact that newer data analysis paradigms, like OLAP and data mining, have been growing in popularity at the enterprise level. Moreover, many existing data extraction, reporting, and analysis processes depend on bulky, expensive, proprietary software, or else have been painstakingly developed with many person-hours. These processes also tend to be geared towards the enterprise. So what if you're in need of an ad hoc solution that will quickly solve small, day-to-day problems? Perl and R can help.

What is R?
R is an open-source, object-oriented system for statistical computation and graphics compatible with the commercial S-Plus program. I stumbled across R a couple years ago when my employer was an SPSS shop. At the time, I didn't feel the to learn about the product. Now I'm working for a smaller company (<50 employees) who simply can't afford them spend $1200 per seat. About a month ago, I finally looked into R. Now I'm hooked!


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