When used successfully, self-service BI tools address one of the biggest frustrations users experience with traditional tools: the lag time between a request for a report or dashboard — or even a simple change to an existing report — and the response to that request from IT or the BI team.
“It’s not just that companies are short-handed on the BI IT side, but it’s also the fact that users increasingly want to do more things with data,” said James Kobielus, senior analyst at Forrester Research Inc. in Cambridge, Mass. Self-service BI is the “hottest segment of the BI market” among his client base, he said. It “gives users their own tools to pull data from source applications directly, or from an intermediary database that IT sets us for users.”
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When IT is taken out of the report and dashboard development process, the BI process is more agile, meaning companies can put their insights into action faster, Kobielus said.
Self-service BI not only puts the power in the hands of the user, but also opens up new ways of analyzing data, Kobielus said. Many users have been exposed to visualization, reporting and modeling to a degree in Excel spreadsheets, but they haven’t been given easy access to predictive analytics tools and statistical modeling. “These self-service BI tools are embedding predictive modeling and statistical modeling in self-serve, highly user-friendly drag-and-drop user interfaces,” he said.
Of course, IT still does a lot of things behind the scenes, as Spott’s approach demonstrates — integrating data, developing templates and showing employees how to use self-service BI tools’ drag-and-drop wizard-driven interfaces.
For Spott, the power of self-service BI is not in its GUI — which he believes is pretty much the same across the available tools — but in how well it handles metadata to connect to multiple data sources. In his view, that is the biggest challenge for IT groups when they choose a data tool. “What I was looking for was a tool that could make dynamic connections on the back end to multiple data sources across multiple platforms,” he said. “That’s where the challenge usually comes in: being able to join different data sources simultaneously.”
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