So, at this level of abstraction, Web Services is a media for transmitting data and information. But the ultimate value to the end-users remains the actual data and information, which then can be absorbed, analyzed and reported through Business Intelligence and other end-user enterprise applications. Like a plumbing network that can handle water or waste with equal efficiency, Web Services can control the volume, speed and direction of data flows. However, they will not discriminate (or even realize) what the content of those flows may be or its relative value.

This, unfortunately, brings us back to the IT cliché of garbage-in, garbage-out. Companies looking at Web Services for the first time, or how to expand them within their enterprises, need to consider what their options are to plug in a data cleansing system to such a Web Services network. Fortunately, data quality management is a field that has also evolved rapidly, and at the most progressive data quality vendors, in step with the development of Web Services.

One of the first things CIOs and data managers need to consider regarding data cleansing and quality is how much budget and developer resources do they want to dedicate to creating the bridge between their Web Services server and their data quality system. They have the option today of customizing those connections via hand-coding, or of selecting a data quality management solution that has already been customized to easily plug into such environments as those from IBM (WebSphere), BEA (WebLogic) or Microsoft (.NET).

One perfect example of this adoption is an international shipping company that uses a data quality management solution to verify and enhance shipping data in a manner that – through Web Services -- facilitates customers’ easily accessing data about the status of their shipments and what shipments are inbound to be delivered to their facilities, along with full detail on who those shipments are from and what they contain.

Another example is the international airline that, in partnership with its affiliated network of hotel chains, car rental companies and travel agencies, needs to share customers’ frequent flyer data, maintaining the accuracy and timeliness of that data. Through Web Services and their data quality soluton, they are able to do this despite the many disparate platforms at those affiliated partner service companies. And they are simultaneously able to receive automatic data feeds on customers’ frequent hotel stays, frequent car rentals and frequent related travel, all of which accrue bonus points for these partner travel-related companies.

So while Web Services are rapidly making our digitized world even smaller and better connected than it had been already, by themselves they simply provide the pipes through which data and applications can be efficiently sent. What is still very much needed as Web Services are deployed is a filtration and processing system to strain out inaccurate or out-of-date data and correct it. Such data quality management (filtration/correction) for Web Services will go a long way towards ensuring the accuracy and value of the data sent over Web Services, and that in turn will further fuel the acceptance and adoption of Web Services.

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