Step 3: Data modeling
Data modeling: Data modeling is an important step in implementing an MDM system. It involves defining the structure and relationships of the data objects to be managed to ensure that the data can be organized and managed effectively.
Here are some steps you should take when modeling data:
Identification of the data objects to be managed
Start by identifying the data objects that will be managed in your MDM system. For example, in the healthcare industry, this could be patients, doctors, medications, medical devices, etc. Capture all relevant information about each data object that is needed in your organization.
Attribute definition
Define the attributes for each data object. These attributes represent the specific characteristics and information that must be captured for each data object. For example, attributes for patients could be name, date of birth, gender, contact information, etc. Make sure you identify all relevant attributes that are required for your business processes and requirements.
Hierarchies and relationships
Define how the data objects are related to each other and how they are structured hierarchically. For example, there could be a hierarchical relationship between medical devices and their components. Also define relationships between data objects, such as the association of a patient with a doctor or the association of a drug with a particular disease.
Data validation and standardization
Define validation rules and standards for the data values. Ensure that captured data conforms to defined rules to ensure high data quality. This may include validation of data types, formats, value ranges, and dependencies.
Adaptation to business processes
Adapt the data model to your specific business processes. Consider the required data flows, workflow rules, and approval processes. The data model should be designed to optimally support your business processes and increase efficiency.
Creation of a logical data model
Based on the above steps, you can create a logical data model that maps the structure, attributes, hierarchies and relationships of your data objects. This logical data model serves as the basis for implementing the MDM system.
Data modeling is an iterative process where feedback from business users and stakeholders should be gathered and changes made to ensure that the data model meets actual requirements and business processes. It is important that data modeling is done carefully as it is the foundation for data integrity, data consistency and effective data management in the MDM system.
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