How do businesses analyze large quantities of data?

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In principle, analytics could be performed using pen, paper and maybe a calculator. But given the huge amounts of data, companies need to sift through today, they do need to rely on information technology. There are many tools available in the market for analytics. The range of analytical software foes from relatively simple statistical tools in spreadsheets (ex-MS Excel) to statistical software packages (ex-Minitab, Statistica) to sophisticated business intelligence suites (ex-SAS, Oracle, SAP, IBM among the big players). Open source tools like R and Weka are also gaining popularity. Besides these, companies develop in-house tools designed for specific purposes.

Good analytical capabilities require good information technology tools to access, integrate and analyze data to transform it into meaningful data-driven insights. However, we need to remember that the tools are actually just that-tools. They are a means to get to what is required. However, it is truly the analyst and how he breaks down the business problem into analytical queries that drives how useful analytics can be for the business.

This article discusses some of the most popular tools in the market today.

Image courtesy of cooldesign at FreeDigitalPhotos.net
Image courtesy of cooldesign at FreeDigitalPhotos.net
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