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What are some best practices for customer data matching, cleansing and integration when your customers are public and private institutions in a variety of industries?

Q: CDI is a hot topic these days, but every CDI solution I read about seems to only address issues related to B-to-C customer data. What are some best practices for customer data matching, cleansing and integration when your customers are public and private institutions in a variety of industries?

Chuck Kelley's Answer:

I think a lot the answers to your questions will be dependent on your goal for matching, cleaning and integration. Some questions that would have to be asked are along the lines of: Do you want to attach to a parent organization or just clean the current one (i. e., Do you want just GMAC or General Motors or both)? Do you want to add specific industry information and if so, just the current one or for the parent organization (i. e., GMAC [Financial Industry] rolls into GM [Automotive Industry])? It all depends on what you want.

For cleaning the current row, most of the cleansing tools (Trillium, Firstlogic, etc.) have a process to deal with that. If you want a more robust requirement, you will likely end up writing some other code.

The reason (I guess) that you don't see more written about B-2-B is that processes are similar enough and most readers will understand the "C"onsumer side as an example better than the "B"usiness side explanation.

Evan Levy's Answer:

There are several companies that address B-to-B issues with their CDI hub products:Purisma, Siperian, DataFlux, and DWL are but a few. It's important to identify the specific data quality issues that you require for B-to-B customer data integration (company/customer hierarchy management, address cleansing and standardization, customer identity management, etc). The benefit that many of these products have is their robust functionality associated with supporting identity recognition and management. Many can leverage a highly flexible and extensible set of processing logic and data element details (address, name, DUNS number, etc.) in determing business identities.


Chuck Kelley is an internationally known expert in database and data warehousing technology. He has 30 years of experience in designing and implementing operational/production systems and data warehouses. Kelley has worked in some facet of the design and implementation phase of more than 50 data warehouses and data marts. He also teaches seminars, co-authored four books on data warehousing and has been published in many trade magazines on database technology, data warehousing and enterprise data strategies. He can be contacted at chuckkelley@usa.net.

Evan Levy is a partner and co-founder of Baseline Consulting Group, a multivendor systems integration and consulting firm. As the partner in charge of Baseline’s largest practice, Levy leads both executives and practitioners in delivering technology solutions that help business users make better decisions. He has led strategic technology implementations at commercial and public sector organizations and advises vendors on their product development and delivery strategies. Levy has been published in a wide array of industry magazines and has lectured on a range of technology delivery experiences at leading conferences and vendor events. He has been a featured speaker at the Marcus Evans Analytical CRM symposium, DCI’s Data Warehousing conference, the CRM Association, DAMA International, the AMA and the Data Warehousing Institute. His current work involves delivering and lecturing extensively on the topic of data integration. You can contact him at evanlevy@baseline-consulting.com.

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