Gartner Magic Quadrant: Data discovery vendors take on BI heavyweights

Data discovery software vendors are stealing market share from the leading business intelligence (BI) players, according to Gartner.

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Independent data discovery software companies are muscling in on territory that once belonged to business intelligence (BI) megavendors like Oracle and SAP BusinessObjects, according to a new Gartner Magic Quadrant report.

The findings represent a sea change in attitude that is being driven largely by business users who want ease of use and who are exerting more influence over BI purchasing decisions than ever before. Historically viewed as a supplement to traditional BI platforms, data discovery software is now increasingly being sought as a viable standalone alternative.

“That ease-of-use dynamic -- the fact that the business users are having greater influence over the purchasing decision -- is really driving the momentum of data discovery vendors like Tableau, Tibco Spotfire, and QlikTech,” said Rita Sallam, a BI research director with Stamford, Conn.-based Gartner Inc. “They’ve been on the Magic Quadrant [before] but this year we’ve seen the momentum pick up.”

Data discovery tools offer many of the same capabilities as traditional BI platforms but are typically much easier to deploy and manage. The products use data visualization-based interfaces that allow business workers to get the intelligence they need without asking the IT department for help with data modeling and report development. As a result, many business workers have shown a willingness to purchase and deploy the technology on their own, even at the risk of creating fragmented data silos, according to Gartner.

The annual “Gartner Magic Quadrant for Business Intelligence Platforms,” which rates the relative strengths and weaknesses of BI software vendors based on the results of customer surveys and interviews, also found that organizations are deploying data discovery tools on a much wider scale than in previous years.

“We’re seeing [data discovery tools used] more pervasively across the enterprise,” Sallam said. “In the past, they were very much departmental solutions. But this year, in particular, QlikTech has really expanded the numbers of average users per deployment.”

Megavendors respond to data discovery momentum

Major BI platform vendors have responded to the success of data discovery software by marketing similar “easy-to-use” offerings. Examples include Microsoft PowerPivot, SAP BusinessObjects Explorer, IBM Cognos Express and Information Builders WebFocus Visual Discovery. PowerPivot has gained the most market traction to date, according to Gartner.

SAP is getting ready to debut the latest version of its flagship BI platform -- SAP BusinessObjects 4.0 -- and says it has a long history of providing business users with self-service capabilities.

“We really pioneered [BI self-service] with a product we call Web Intelligence,” said Dave Weisbeck, SAP’s senior vice president of BI and enterprise information management. “In our Explorer solution, [we] really tried to simplify that even further.”

Explorer will be fully integrated with SAP BusinessObjects 4.0, which is set for release Feb. 23.

“I wouldn’t quite say [Explorer] is reactive to what we’re seeing in the market,” Weisbeck said. “But we’re certainly aware of that evolution [and] trying to stay ahead of that as well.”

Data discovery software: Words of warning

Before rushing in and purchasing a data discovery software platform, there are some important considerations to keep in mind, according to Sallam.

For starters, data discovery tools vendors claim that users do not need to back up their products with expensive data warehouse platforms -- and that approach may be fine for some small organizations. But generally accepted best practices dictate that a data warehouse is usually in order, Sallam said.

“You are likely to have a portfolio of tools, and to be able to manage that effectively you have to have a data warehouse structure where there is a corporate-sanctioned way to view data,” she said. “While it’s possible to use these tools without a data warehouse, it would not be best practice.”

While it may seem counterintuitive, it’s also important to remember that data discovery tools tend to be more expensive than traditional BI platforms on a cost-per-user basis, Sallam said. Companies may end up paying more for traditional BI platforms, because those deployments tend to be much larger, but the cost of supporting individual users currently tends to be higher with data discovery tools.

Data discovery vendors also have more work to do to in the areas of scalability, security and administration if they want their products to be ready for very large-scale enterprise deployments. Traditional BI platforms are more mature than their data discovery counterparts and have evolved such features to the point where they can support thousands and thousands of users.

“I think that would be the biggest caution for large enterprises that have very large numbers of users,” Sallam said. “The data discovery tool paradigm might be at best a complementary strategy at this point until the platforms become more very-large-enterprise ready.”

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