The most frequently mentioned domains within Master Data Management (MDM) are customer, product and location. Data quality is a core discipline when working with MDM. In data quality we talk about different dimensions as uniqueness, relevance, completeness, timeliness, precision, conformity and consistency.

While these data quality dimensions apply to all domains of MDM, some different dimensions apply a bit more to one of the domains or the intersections of the domains.

Below is a figure with an attempt to illustrate where the dimensions belong the most:

Uniqueness is the most addressed data quality dimension when it comes to customer master data. Customer master data are often marred by duplicates, meaning two or more database rows describing the same real world entity. There are several remedies around to cure that pain. These remedies are explored in the post The Good, Better and Best Way of Avoiding Duplicates.

With product master data, uniqueness is a less frequent issue. However, completeness is often a big pain. One reason is that completeness means different requirements for different categories of products as explained in the post Hierarchical Completeness within Product Information Management.

When working with location master data consistency can be a challenge. Addressing, so to speak, the different postal address formats around the world is certainly not a walkover. Even google maps does not have all the right answers as told in the post Sometimes Big Brother is Confused.

In the intersection between the location domain and the customer domain the data quality dimension called precision can be hard to manage as reported in the post A Universal Challenge. What is relevant to know about your customers and what is relevant to tell about your products are essential questions in the intersection of the customer and product master data domains.

Conformity of product data is related to locations. Take unit measurement. In the United States the length of a small thing will be in inches. In most of the rest of the world it will be in centimetres. In the UK you can never know.

Timeliness is the everlasting data quality dimension all over.

When we talk about multi-domain Master Data Management (MDM) we usually recognize party (customer, supplier, employee) and product as the most predominant domains. The location domain is also widely understood as a separate domain. Further we can discus about assets as done in the post Where is the Asset.

Then there is the Calendar domain. In many industries calendar may just be seen as configuration data. However, in some industries calendar is a true master data domain.

One example is in postal services as mentioned in the post The Path to Multi-Domain MDM.

Another example is public transit, an industry I have worked with in the last 16 years. Managing calendar data has many challenges in running a business or authority in public transit. Some tricky points are:

• Keeping track of day types where different partners sees the week and public holidays differently, not at least when crossing borders.
• Changing the day not necessarily at midnight, but at various times.
• Assigning and monitoring services to a schedule under these circumstances.

In public transit managing calendar data has the same issues as the other more common master data domains, as calendar data may be represented differently in applications across the IT landscape stretching from back-office systems to mobile devices on-board vehicles, as examined in the post Going in the Wrong Direction.