Its a food-processing company.
Like lots of companies in these days of consolidation, it worried about melding two merged companies collections of databases, legacy applications and data sets.
With some 7,000 employees, six processing plants and a tidy collection of farms, getting to a centralized data repository meant gluing together separate ledgers, separate payrolls, separate inventories—really, the whole nine yards, with the added worry of cleansing data and deciding whether business processes would need to change.
The company got there. The entire suite of products in IBMs newly acquired Ascential line is now chugging away, doing data cleansing, transformation, staging and loading beneath a data store that runs between 20GB and 30GB and will hit about 200 by the time theyre through.
A data integration specialist who requested anonymity said the company is doing it the IBM way—federated, with data staying put on Microsoft Corp. SQL Server databases, and they are, yes, getting what enterprises keep saying they want: one version of the truth.
The company is a happy customer. But is its story in fact a reflection of the data-integration nirvana that IBM and other companies are hyping?
In that version, integrating the processes of IT and integrating business processes no longer belong to siloed products.
In their place, we have platforms, like IBMs WebSphere group of products, that promise to do it all: ETL (extraction, transformation and loading), EAI (enterprise application integration), EII (enterprise information integration), data quality and data profiling.
The food-processing companys situation, like other Ascential customers, is not, in fact, indicative of this nirvana.
Rather, they are satisfied customers on IBMs IT-process side of things.
Some such customers are looking wistfully toward the promised land of mega-data-integration, but they dont believe that theyll get there anytime soon, and they dont even think that were all using the same definition of the things we need to get there.
"When I say metadata, and this is perhaps specific to the [data] warehousing construct, its not just data lineage," said Danny Siegel, senior manager of Finance Business Technology at the pharmaceutical giant Pfizer Inc., which is another Ascential customer.
When Siegel refers to "data lineage," he speaks about the IT-process side of data integration, where metadata describes things such as where data originally resided, who touched it when, and other things relating to its journey from its database source toward its end destination in the data warehouse.
What he does mean when he says "metadata" is the business side of things: the business logic that explains the end-stage data in plain English, in plain tell-it-to-the-executives speak.
"When we say metadata, were describing business process and logic," Siegel said. "Thats what the problem is, for us: You have a metric at the end of the road in a warehouse. It gets there somehow. Theres a technical aspect to it. Theres a business aspect to it. The technology cant be communicated to anybody but an analyst. How do you make it intelligible to … executives?"