The IT and business alignment is a widely discussed challenge of data integration. The major data integration problem adds up to this: define customer.

Data from different functional areas doesn’t join up: sales orders are associated with the newly contracted customers, but the marketing campaign data is associated with prospects. Is a customer someone who’s actually bought something from you, or is a customer someone who’s interested in buying something from you? Should a definition include a certain demographic factor that reflects your typical buyer? If sales, marketing, service, and finance can all agree on a single definition of customer, then all the associated transactions could be easily integrated.

The thing is that all these specialists have their understanding of the word “customer”. That is why it is next to impossible for them to agree on a single definition and you have to somehow manage data integration without it.

To solve this issue, you can define what each functional area (and each CRM system) means by “customer”. This is how we know that customer data coming from a marketing system includes prospects, as well as existing customers. With this information, you can build a semantic model to understand how the different definitions of customer relate to one another.

Using this model, it would be possible to associate supply data with parts, cost data with product class, marketing data with brands, and so on. The relationships among these entities allow for data integration from different functional areas. This semantic model may be complex, but try to accept it and don’t head for simplifying it. The world is complex. Data integration requires a sophisticated understanding of your business, and standardizing vocabulary is not going to be the right answer to this challenge.