Once you have determined that your organization can achieve the benefits of integrating data quality and data governance through introducing a master data management (MDM) program, some typical early questions emerge, such as “What architectural approaches will we take to deploy our MDM solution?” or “What are the business approaches for acquiring the appropriate tools and technologies required for MDM success?” These are good questions, but they are often asked prematurely. Even before determining how to manage the enterprise master data asset, there are more fundamental questions that need to be asked and comprehensively explored, such as:

• What data elements constitute our “master data?”
• How do we locate and isolate master data objects that exist within the enterprise? How do we assess the variances between the different representations in order to consolidate instances into a single view?

Because of the ways that diffused application architectures have evolved within different organizations, it is likely that while there are a relatively small number of core master objects used, there are many different ways that these objects are modeled, represented and stored. For example, any application that must manage contact information for individual customers will rely on a data model that maintains the customer’s name. Yet one application will track an individual’s full name, while others will break up the name into its first, middle and last parts. And even for those that track the given and family names of a customer will do it differently – perform a quick scan of the data sets within your own organization and you are likely to find “LAST_NAME” attributes with a wide range of field lengths.