IBM’s Project Neo Aims to Make Visualization Easy

“According to this graph, we’re doomed! Doomed, I say!”

IBM Labs is working on a new initiative, “Project Neo,” that it hopes will give workers a better grasp of data analytics.

Project Neo layers a simple dashboard atop datasets, allowing untrained workers to create visualizations and ferret out patterns and insights from raw data. The focus is on speed, thanks in large part to IBM technologies such as Rapidly Adaptive Visualization Engine (RAVE). IBM plans on launching the software Beta in early 2014.

The project is just one aspect of IBM’s latest visualization projects, which includes elements of the Cognos Business Intelligence portfolio that allow report authors to augment data with a library of rendering tools.

IBM clearly has the resources to play in many areas of “Big Data,” but this renewed emphasis on making analytics easy for everyday employees—and not just data scientists or analysts—is clearly designed to help Big Blue battle it out with a growing pack of startups and well-established firms that market easy-to-use analytics software.

Take Splunk, for instance, which is working to make Hadoop more accessible to “regular” workers with Hunk, a platform for analyzing and visualizing data in Hadoop, the popular framework for crunching unstructured datasets spread across substantive hardware clusters. Or any number of other analytics tools that don’t necessarily require a Ph.D to run (although most do necessitate some degree of training).

Software companies want to make their analytics products more usable in order to boost adoption, which in turn increases revenue and profits. A study by research firm Forrester earlier this year suggested that dashboards are a top priority for companies investing in business-intelligence software.

“Many nascent technologies will see rapid adoption and move out of their current niche usage,” Forrester analyst Charles Green wrote in a July 15 corporate blog posting. “The hype surrounding many analytics technologies—such as predictive analytics—masks the reality that their adoption and usage currently remain limited to some relatively specific instances.” Forrester believes that budget is a major impediment to layering more analytics technologies atop businesses’ datasets.

But user-unfriendly systems, coupled with lack of training, can become equally insidious blockers. An increasing number of IT firms seem to recognize this; it’s likely that Project Neo will face quite a bit of competition next year.


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