Article

SaaS-based data quality and integration tools gaining momentum

Jeff Kelly

Cost and flexibility may be trumping security concerns when it comes to Software as a Service (SaaS) and corporate data, as the on-demand deployment model is beginning to gain a foothold in the marketplace,

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according to Gartner Inc.

In particular, on-demand data integration and data quality software showed signs of breaking into the mainstream, with 28% of companies that responded to a recent Gartner survey indicating that they have deployed SaaS-based data integration tools, and 24%, SaaS-based data quality tools.

According to an accompanying Gartner report, the SaaS deployment model makes experimentation with emerging technologies, including data quality, "less risky and gives enterprises a head-start over competitors," fueling adoption. For the survey, Gartner polled around 500 data managers in six countries.

SaaS-based, or on-demand, technologies are usually accessed over the Internet and require little in the way of on-site hardware support or long-term contracts. As companies increasingly turn to SaaS-based applications for customer relationship management and enterprise resource planning functions, they are also looking to on-demand-style data quality and integration tools to populate them with data from in-house legacy systems.

A number of data management technology vendors have begun offering SaaS in the last few years, often aimed at cash-strapped small and midsized business that nonetheless have pressing data integration and analytics needs.

Trillium Software, for example, has made its global name and address validation tool and batch and real-time integration services available on-demand, while Informatica offers customers a line of integration services built specifically for the SaaS model.

"When it comes to SaaS integration and cleansing, the people that need it and use it most are somewhat different than enterprise customers," said Ron Papas, general manager of Informatica's on-demand business unit. Most first-time SaaS-based data integration deployments are initiated by business units, not IT, so "we've created solutions specifically for the on-demand market from the ground up," he said.

Cast Iron Systems, which specializes in helping companies integrate data from legacy systems to SaaS-based applications, recently launched Cast Iron Cloud, an on-demand, cloud-based integration service that lets customers easily connect legacy data sources, such as SAP or Siebel databases, with SaaS-based applications.

SaaS-based application vendors are also looking to partner with data integration and quality specialists to differentiate their offerings from competitors, according to Chandar Pattabhiram, vice president of product marketing at Cast Iron Systems. Gearworks, a Minneapolis-based on-demand mobile software vendor, for example, works with Cast Iron Systems to integrate its customers' data.

Gearworks initially approached Cast Iron Systems two years ago to help it integrate its own data with Salesforce.com, but the company soon realized that the integration services could also improve Gearworks' customers' integration processes, according to Rob Juncker, co-founder and CTO of Gearworks.

"Our core competency is mobility and taking mobile devices and making them more productive," Juncker said, adding that it is not cost effective for Gearworks itself to spend time and money on specialized data quality and integration processes. "Cast Iron not only gave us the tools but credibility to the entire application integration infrastructure."

SaaS stands to gain in down economy

The current dismal economic climate could make SaaS-based data management software an even more inviting option for many companies, as they struggle to secure capital in tightening credit markets.

"The barrier to adopting SaaS alternatives is low, with typically reduced startup costs, no license investment and no hardware investment needed," the report stated.

Overall, Gartner predicts that the SaaS-based software market, including data management technologies, will reach $19.3 billion by the end of 2011, up from $6.3 billion in 2006.

This doesn't mean that traditional, on-premise data management technology deployments are on the way out, however. The survey found that most companies use a mix of on-premise, outsourced and SaaS-based technology to meet their data management needs, with 65% to 75% of respondents employing on-premise software.

Especially for large enterprises, on-premise software "will remain popular for a variety of reasons, including the need to build custom software and the need for greater data security in some environments," the report said.

The survey also found that companies were less inclined to deploy SaaS-based business intelligence (BI) and data warehousing technology, with only 18% of respondents indicating they had done so.

The slower adoption rate of BI and data warehousing technologies is due largely to the fact that "companies have had in-house implementations of this type of software for a long time, so SaaS will have more difficulty displacing a proven deployment model."

SaaS data management tools not always as robust

While SaaS-based data management tools are appropriate in some cases, Gartner warns customers that SaaS-based software, at this point, often trails its on-premise counterparts in maturity and capabilities.

Business Objects, which was acquired by SAP earlier this year, has offered its flagship BI platform, Business Objects XI, to customers via an SaaS-based model since April 2006. Pierre Leroux, product marketing manager at Business Objects, said the company aims to match its SaaS-based capabilities to that of its on-premise software, but he seemed to acknowledge that it won't happen overnight.

"We're trying to offer a similar experience that a customer would get with an on-premise [deployment]," Leroux said. "So whenever there's a new capability for the platform, it will eventually trickle down to the SaaS offering."

The report also highlighted the deficiencies of SaaS-based data quality tools, which – according to Gartner -- can't yet provide the full range of capabilities required by most companies despite an increasing adoption rate.

In addition to carefully evaluating its capabilities, companies considering SaaS-based data management technology should target specific, repeatable, enterprise-wide tasks, according to Gartner. "In other words, plan SaaS deployments enterprise-wide to guard against siloed investments that cannot support growing business needs," the report said.


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