Informatica Data Quality Blog

Posted by Chris Cingrani in: Data Quality > Benefits

On May 15th, Informatica completed the acquisition of Identity Systems, a pioneer in identity resolution technology allowing customers to search and match identification data across multiple systems and more than 60 languages. As someone who has been in the data quality space since 2001, I remember encountering Identity Systems in various sales cycles when they were known as Search Software America (SSA). In each instance, I recall that the level of sophistication around matching they offered was something that was difficult to compete against. If we could expand the data quality discussion to include other aspects, such as cleansing and validation, we had a much better chance in the proof of concept or sales cycle.

Continue reading "Identity Systems Acquisition – the Next Evolution of Data Quality" »

Posted by Chris Cingrani at 04:20 PM | Permalink | Comments (0) | TrackBacks (0)

Posted by Tom Golden in: Data Quality > Benefits ; Data Quality > Best Practices ; Data Quality ; Data Quality > Technology

Looking in Webopedia.com recently I came across a definition for CDI. Yes webopedia.com - it bills itself as the #1 online encyclopaedia 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.

Continue reading "You can’t have CDI without Data Quality" »

Posted by Tom Golden at 02:13 AM | Permalink | Comments (0) | TrackBacks (0)

Posted by Larry English in: Data Quality > Benefits ; Data Quality > Best Practices ; Data Quality ; Data Quality > Management ; Data Quality > Monitoring

I recently received an email from one of my early clients. After having worked in four different companies in four different industries, she came to a sad conclusion, writing:

“The thing that they all have in common is a desire to cut corners and deal with quality later. It takes a lot of energy to be the information quality cheerleader, and I find it discouraging and overwhelming at times. Keep writing your articles and books to encourage all the people like me who are dealing with these issues every day.” P. G.

The discovery that P. G. has experienced is, unfortunately, the norm—not the exception. There are two critical elements in this experience.

Continue reading "Information Quality & Management Transformation" »

Posted by Larry English at 07:59 AM | Permalink | Comments (2) | TrackBacks (0)

Posted by Garry Moroney in: Data Quality > Benefits ; Data Quality > Best Practices ; Data Quality ; Data Quality > Management

Determining the aggregated return on investment for a data quality management initiative is notoriously difficult. Typically a minimum or partial ROI can be estimated by reference to the impact of low quality data on one or two key projects or processes. For example in a CRM project data quality ROI can be tied to reductions in customer contact failures and increased sales due to high quality segmentation. But given that the same set of master data will be used more than once in most organizations (i.e. customer master data will also be used in the billing system, the supply chain system and so on) and will add value (or destroy value!) in all of these processes, basing your ROI calculations on a single system or process will always underestimate the true returns.

For an organization trying to estimate the total returns across the enterprise from a data quality initiative, there are two difficult questions that must be addressed:

• How valuable is this dataset to the enterprise - assuming 100% data quality?
• How does its value decrease as quality erodes?

While these questions might at first seem unanswerable, it is worth noting that these are not unusual questions for a business to ask. In fact businesses need to be able to answer questions of worth and depreciation for all their tangible assets - property, stock etc.

Unfortunately data is one of those intangible assets where normal valuation approaches like recorded cost or replacement value are ineffective. But there are other intangible assets such as IPR, work-in-progress, customer and partner relationships (good will) where significant research has been done to develop effective valuation methodologies. It just might be possible to leverage these methodologies to value your data. For example, the value of customer data is directly related to the value of the customers themselves and so "customer lifetime value" methodologies should be applicable in estimating the value of customer data and the extent to which this value varies with data quality.

Have any of you out there attempted to put a real value on your company data in this way? Perhaps you'd be willing to share your experiences with us.

For more information on building a business case for data quality and calculating potential return on investment see the Informatica white papers: Data Quality Profiling Calculating ROI for Data Migration and Data Integration Projects
and The Data Quality Business Case—Projecting Return on Investment.

Posted by Garry Moroney at 03:36 AM | Permalink | Comments (3) | TrackBacks (0)

Posted by Larry English in: Data Quality > Benefits ; Data Quality

What would happen if your knowledge workers returned from the holidays and when they “opened” their data marts, they found nothing but high quality information? No missing information to have to hunt for. No wrong information to have to correct. No misleading information to cause them to make the wrong decision.

Imagine what it would be like if people could do their value work without hunting for, correcting, or recovering from failure caused by poor quality

Continue reading "The Gift of High Quality Information" »

Posted by Larry English at 01:32 PM | Permalink | Comments (0) | TrackBacks (1)