Informatica Data Quality

Looking in Webopedia.com recently I came across a definition for CDI. Yes webopedia.com - it bills itself as the #1 online encyclopedia dedicated to computer technology. You might wonder what I was doing surfing this font of knowledge - well I had time on my hands between delayed flights coming back to Europe from the US. You know what they say "time to spare, travel by air."

The Webopedia.com CDI definition went: "Short for Customer Data Integration, it is the combination of the technology, processes, and services needed to create and maintain an accurate, timely and complete view of the customer across multiple channels, business lines, and, potentially, enterprises, where there are multiple sources of customer data in multiple application systems and databases."

A bit long winded perhaps, but the three words that shone out at me through the glare of the florescent lights in San Francisco airport were "accurate, timely and complete"; all data quality issues. Despite this, few if any of the Customer Data Integration (CDI) vendors in the market today have truly addressed the data quality issues in their CDI solutions. And anyone who has gone down the route of developing their own custom-built CDI application will be all too familiar with the data quality demands involved.
CDI or customer data hubs, a subset of the wider master data management field, have become a focus for large organizations struggling to improve customer service and the operational efficiency of all customer interactions. Like all complex IT projects the CDI vision can be limited by the usual constraints of inadequate budgets, tight timelines and capabilities. In the pressure to get the CDI project completed organizations have a tendency to push the data quality issue to the side, and also to take more tactical than strategic views of the CDI implementation.

I would argue that this is a mistake; if you want to create a successful customer hub it is essential to focus squarely on data quality and take as broad a view as possible in terms of CDI strategy – especially in the planning phase.

So even if you don't have time on your hands, and you are pressed to the pin of your collar to implement the project sooner rather than later, don’t forget the data quality. Defective data quality not only limits return on investment (ROI) from a CDI implementation, but it will ultimately lead to outright failure of the solution. The CDI project will not alleviate the problems that can mean poor relationships with customers, vendors, suppliers, regulators, and other stakeholders which can result in poor decisions and missed business opportunities.

On the other hand when data quality is central to the CDI implementation, the business benefits can be vast: increased customer satisfaction, greater customer loyalty, improved revenue and profit, decreased operational costs, and greater regulatory compliance.

At the end of the day I believe that the ultimate success of CDI hinges as much on good data quality as it does on anything else.