What are the different types of data models used in IT service design?

1 Conceptual data models

A conceptual data model is a high-level representation of the data requirements and concepts of an IT service domain, without specifying the details of how the data is stored, accessed, or manipulated. A conceptual data model usually uses graphical symbols and natural language to describe the entities, attributes, and relationships that are relevant to the IT service objectives and scope. A conceptual data model can help you to understand the business context and needs of your IT service, and to align your data design with the service strategy and vision.

2 Logical data models

A logical data model is a more detailed and formal representation of the data involved in an IT service, using a specific data modeling notation and terminology. A logical data model defines the types, properties, and constraints of the data elements, as well as the logical relationships and rules among them. A logical data model can help you to validate and refine your data requirements and concepts, and to ensure consistency and accuracy of your data design across different IT service components and layers.

3 Physical data models

A physical data model is a representation of how the data is actually stored, accessed, and manipulated in a specific IT service environment, using a specific data technology and platform. A physical data model specifies the physical structures, formats, and locations of the data elements, as well as the physical operations and processes that manipulate them. A physical data model can help you to optimize the performance, security, and reliability of your data design, and to implement and maintain your data solutions in your IT service infrastructure.

4 Data flow models

A data flow model is a representation of how the data moves and changes through an IT service process or function, using graphical symbols and arrows to indicate the sources, destinations, transformations, and controls of the data flows. A data flow model can help you to identify and analyze the inputs, outputs, and dependencies of your IT service activities and functions, and to design and improve your data integration and quality management.

5 Data lifecycle models

A data lifecycle model is a representation of how the data is created, used, maintained, and disposed of in an IT service context, using a series of stages or phases to indicate the different states and transitions of the data over time. A data lifecycle model can help you to plan and manage the data governance and compliance aspects of your IT service, and to design and implement your data retention and disposal policies.

6 Data value models

A data value model is a representation of how the data contributes to the value creation and delivery of an IT service, using metrics and indicators to measure and evaluate the impact and outcomes of the data on the IT service performance and quality. A data value model can help you to align your data design with the IT service value proposition and objectives, and to monitor and improve your data value realization and optimization.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?