Cool Vendor List Reveals Three Data Integration, Management Trends for 2008

Loraine Lawson spoke with Ted Friedman, vice president of research for Gartner, who recently co-authored an annual Cool Data Integration Vendors report, part of a series on vendors offering unique solutions.

Lawson: What are the criteria for judging who is a cool vendor, and who is not?
Friedman: There are loads and loads of vendors we think are cool, but we try to focus this annual cool vendors research on a small subset within each functional area. My area being data management, we try to focus on a small set of vendors that we think really highlight some of the key trends, but the three main criteria are the following: The vendor has to be delivering technology that we believe to be innovative - it is going to let people do things that they could never do before, that's the innovation criteria. This second one is that it's going to be impactful, right? So this is not just about technology for the sake of technology. We're looking for innovative technologies that will also have significant business impact, that they're going to deliver value somehow. So, innovative, impactful, and the third category, which is sort of a subjective one I'm sure, is that it needs to be intriguing in the sense that it has captured our curiosity within the last six months or so. So, contemporary and eye-catching, if you will.

So at the high level, those are the three criteria, and then I could say within my area of data management here, which is in itself quite a broad space, you've got databases, you've got integration, you've got quality and a number of other things. We try to write about a mix of cool vendors that cover more or less the breadth of the topics within that data management space. I don't think we've perfectly achieved it in this go-round of the cool vendors thing, but we did get pretty good breadth. You know, you've got everything from database-oriented vendors like illuminate to data integration guys like Nimaya to data quality like Infogix and so forth.

Lawson: When you look at this, are you looking at products that people can expect to see this year, or ones that are already out?
Friedman: Oh, these are things that already exist. We're talking about vendors here that are very often in a startup kind of mode, they have at best a handful of customers, at a very early stage in their maturity in the market, but the technology absolutely exists.

Lawson: So what are the cool trends?
Friedman: I think one of the biggest trends we see in the face of data management, and there are several, is organizations try to better understand and make sense of the data assets they've caught. Everybody is piling up loads, and loads, and loads, terabytes, and terabytes worth of data, and the volumes of data have more or less begun to strip our ability as humans to really understand and use it because we can't find what we need, we can't make sense of what's there.

So, I think some of the technologies we're seeing emerge in this space began to speak to this idea of how to better leverage, how to better make sense of, and how to ensure the quality of, or that we can trust all that information. And so we've got guys like illuminate and Dataupia, who in effect provide technology to allow us to sift through bigger volumes of data in a more time-efficient fashion. So, our queries against the data, against massive volumes of data, we can actually get meaningful results back. If the data volume escalates exponentially, the technology these guys are delivering is aimed at trying to keep the problem tractable, bounded enough that we can still try to get some value and make sense of the data.

A second big trend is quality of data, and we're seeing organizations begin to invest very heavily, although they've invested over the years to a less strategic degree, but investing a lot in measuring and trying to improve the quality of the data that they are dealing with. So a growing interest in schools and technologies aimed at measuring the quality of data, and alerting or identifying cases where quality of data has fallen out of spec, and proving or fixing flaws in the quality of data. One of the vendors in the cool vendor list here, Infojix, provides technology to, in effect, identify quality flaws in data.

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