Schema modelling is the process of creating a data model for the “customer” in the Pretectum CMDM. We describe the customer modelling process as “schema definition”.
A database schema is one that contains a list of attributes and instructions to tell the database engine how the data is organised. The intention of the Pretectum CMDM is not to define all the complex relationships between all customer-related data objects but rather to prescribe a data structure that will serve the objectives of the business.
In the Pretectum CMDM, the data model can be considered abstract.
The schema definition that you have in the CMDM for the customer, is a model that elaborates the key characteristics of the customer master in terms of the field names and ultimately ties to any data that you choose to place within the system via associated datasets.
A typical customer master schema encompasses title, names, addresses, contact methods and perhaps some special identifiers like account IDs, social security numbers, date of birth and others.
The reason the Pretectum CMDM starts with a model is that we expect that the model will shape the data that define, capture and control the customer data that matters most to the business.
We have business purposes that you have in mind at the core of the schema definition which may be implemented technically, in conjunction with your systems to provide data quality assurance. If the entire customer entity model were to be defined within the C-MDM, it might contain a great deal more characteristics than you might need. The model may result in attributes that are not a central focus of a shared repository that diverse stakeholders might need.
Support for complexity
The Pretectum CMDM recognises that in some instances, the single-entity schema may be over-simplistic for the purposes of a given business and that different groups within an organization may have different descriptors in mind for the customer. One department may refer to the customer descriptor as Name, another may refer to that as Full Name.
The Pretectum CMDM will allow an alternative interpretation to be possible by making reference to a central model and leveraging data classifier tags. The central schema model will support schema definition aliases or alternative definitions and descriptors as cascading and dependent alternative schemas. These alternates can be either within a separate business area or within the same business area. The approach a business may choose is entirely at their discretion.
In some cases, the decision might be needed to produce a clone of an existing schema and instantiate a complete independent schema and establish a translation or transformation design if data needs to be exchanged between datasets.
Configuration options
Ultimately the definition of schema encompasses a great many attributes including whether nulls are permissible, which attributes are keys, whether they need to be unique, the data type, the string lengths and then more advanced configuration such as range validity and acceptable values, formats and patterns.
More complex scenarios can encompass limited cross attribute dependencies but ultimately the intent is not to replace all the configuration variations that your core CRM, ERP and CDP systems support since they are driven heavily by reference data that evolves over time.
In addition, the schema definition allows the support of the establishment of the customer glossary and data quality value and weighing indicators. These metadata attributes are also more advanced use case options but the intent is ultimately to feed your integrations and reporting needs according to a hub and spoke model, wherein the Pretectum CMDM functions centrally to your systems and solutions that house and leverage customer data.
To learn more about the Pretectum CMDM contact us today.