The Future of Business Intelligence: Statistical Analysis

Today on TIP: Next Generation Business Intelligence: Statistical Analysis Tools and Data Science: It’s About More Than Tools.

In his latest feature for Tom's IT Pro, cloud specialist Dan Sullivan poses the following question: Now that you've built a data warehousing infrastructure and created an array of management reports what will you do next? Well, its time to take advantage of the latest and greatest in Business Intelligence solutions to make the most out of the data at hand.

"Both statistical analysis and business intelligence (BI) reporting tools can quickly help you  get a handle on general characteristics of a data set. For example, it’s a simple matter to find an average or get a sense of the shape of the distribution of a numeric attribute," Dan writes. "Many BI reports are designed to summarize and aggregate data in different subgroups.  With reports like those, you can readily find thetop performing product lines, identify poorly performing sales staff, or get a sense of how varied performance is between regions."

So, as Dan notes, statistical analysis tools such as SAS, IBM SPSS and R can assist you in uncovering insights from data that may not be apparent in your average management reports.

See here to read the full article, the first in a two part series. Next up: Dan will address Data Mining and Business Intelligence.

Also, check out Dan's latest post to his The Silver Lining Tom's IT Pro blog.

In it, Dan comments on recent salary survey by business intelligence solutions provider SiSense. The survey focuses on the emerging IT job role of Data Scientist. 

It found that salaries are up worldwide. And, as you'd expect, the more education and experience Data Scientists have, the more they earn.

So life is good for the Data Scientist, "at least in the short run and maybe even in the medium term," writes Dan. "The long run is not necessarily so positive it you don’t have the right skills."

Dan wrote earlier about learning the right skills to be a data scientist, while others have  written on the role of Hadoop in big data and data science.  But learning software is not enough, according to Dan.

Get the full story here in The Silver Lining.

Dan Sullivan is an author, systems architect, and consultant with over 20 years of IT experience with engagements in systems architecture, enterprise security, advanced analytics and business intelligence.

James Alan Miller is Managing Editor of Tom's IT Pro. He is a veteran technology journalist with over seventeen years of experience creating and developing magazine and online content. Founding editor of numerous business and enterprise computing sites at the internet.com network, James headed up the After Hours section at PC Magazine, as well as hardware and software sections of various Windows publications.

See here for all Tom's IT Pro articles written by James.

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