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Data Quality Tools Consolidation Continues

I just read a press release that said that Pitney Bowes "has signed a definitive agreement to acquire all of the remaining
outstanding shares of Firstlogic for approximately $50.3 million." Firstlogic, one of the few remaining independent data quality tools vendors, will now become a wholly-owned subsidiary of Pitney Bowes, which acquired data quality tools vendor Group 1 a year ago April. It will interesting to see how, if at all, the two tool suites will be combined. Note that prior to Group 1's acquisition, Group 1 itself had acquired ETL vendor Sagent. Is Pitney Bowes looking to get into the ring with IBM on the ETL/Data Quality Front?

What does this bode for the DQ Tools industry?

Trillium, which is owned by information provider Harte-Hanks, recently purchased data profiling tool vendor Avellino. Ascential, full on a dinner of Metagenix, Vality, and Torrent, found itself on IBM's dinner plate. Evoke, which had sold its remaining assets to COnversion Services about a year ago, just was passed along to European Data Quality company Similarity Systems. SAS bought DataFlux a few years back.

One might consider this evidence of one of two things. The first thing is that data quality technology has matured to the point where it is deemed critical to the information movement process. IBM's acquisition of Ascential and DWL provides end-to-end coverage of the information chain all the way to the end-user, while Pitney Bowes may be repositioning itself to break into that market as well. There is little information on upstart ETL vendor Ab Initio, but one might surmise they have some tricks up their sleeves in the data cleansing arena, between development and partnerships.

The second thing might suggest that data quality tools vendors are not able to establish a healthy market standing on their own two feet, or else there might not be such a preponderance of acquisitions.

Most likely, a combination of a desire on behalf of larger information vendors (e.g., IBM or Harte-Hanks) to incorporate data quality into their bags of tools indicates the clarity of the importance of data quality, and a need to keep the good DQ tools vendors healthy is what is driving this continued consolidation. And this echoes a lot of the sentiments I have been saying in a number of my columns, articles, and appearances over the past 4 years.

Where else might it go? Here are some things that I see in my crystal ball for the next few years:

- Continued acquisitions in the Data Quality Space

- Look to see the big guys gobbling up more innovative tools vendors on the periphery, such as Metadata management, Semantics and Taxonomy management, and Customer Data Integration.

- Larger vendors (e.g., Oracle, SAP, etc.) may be developing their own suites of data quality tools, or look for ways to divorce themselves from recently acquired partners

- Look for more innovative ("second generation") data quality management tool vendor start-ups that will look more and more attractive to large conglomerates like IBM, Oracle, Informatica, Business Objects, etc.

Oh, and on that last note: anyone have any seed capital? I've got some great ideas a-brewin' ;-)

  Posted by David Loshin on September 1, 2005 7:45 AM |

Comments

I think "critical to the information movement process" is the key observation that really is the main story here.

During my past 17 years in this field I've seen data quality in general, and Customer Data Integration (CDI) in particular, emerge from being data warehousing after-thoughts to being themselves the actual drivers of ED projects.

"Customer centricity" in particular is receiving strong mind-share at the excecutive level around the world, and this kind of technology lies at the heart of those kinds of applications.

Seeing all these independent vendors being acquired by the big players over the past few years really drives home the fact that this is no longer a "niche business" or passing fad, but instead represents a major strategic evolution that will provides tremendous opportunities for years to come.

- Ed Allburn, Pres/CEO
www.DataDelta.com

I think Google's hiring frenzy may also be a factor, as noted here (http://www.cdistation.com/2005/09/thoughts-on-dq-consolidation.html) on CDIstation. It would be hard to build one of these companies today!

It seems we've come full circle. I saw a presentation from an analytics vendor that claimed that analytics drive DQ, as opposed to the other way around. Instead of analytics projects failing because of DQ problems, they're seeing increased efforts on DQ because of increased visibility.

I am co-editor for the newly evolving draft ISO Std 25012 on Data Quality. It is not very robust at the moment and deliberately so. We cannot include any tools, vocabulary, techniques for data cleansing, enriching, transforming, matching, etc.that might be construed as an endorsement of a private enterprise. However, we are looking for generic descriptions to use as informative guidance for the Annex that might describe the processes of cleansing/enriching/transforming, i.e., the use of arrays, filters, mathematical manipulations such as cardinality analyses that are used by the DQ industry in general. Is there such a generic description available? ISO pays no royalties, however, any non-proprietary examples that may be used will be given full attribution in the standard. No copyrighted material can be used. Anything submitted must contain a permission to republish release. I can be reached at michael.p.kress@boeing.com

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