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Why conceptual data model is important?

Why do you need conceptual data model?

  • It describes exactly the information needs of the business.
  • It facilitates discussion.
  • It helps to prevent mistakes, misunderstanding.
  • It forms important “ideal system” documentation.
  • It forms a sound basis for physical database design.
  • It helps in forming sound logical data and functional models.

Business people define the process to achieve their business goals. Process has set of defined activities and drivers for those activities are data inputs and data outputs. What happens if we don’t define the required data entities in the early stage? Business expects some output from their process definition and if we have not defined the data entities as parallel process during process definition, it is very much likely that the output defined for a process will not match the expected result.

Below picture (figure-1) explains it all, assume you want to build a house which you had dreamed for long and you hired a contractor to build the house.

 

1. Dreams and Reality

 

Figure -1:,

 

Assume contractor didn’t hire an architect to design the house, hence he will not have proper specification. Now you are at the mercy of mason who may or may not be very experienced, builds the house with his own specification by using his gut feelings. There the reality speaks. Similarly, to execute any business successfully, definition of related and important data is crucial.

 

A conceptual data model is not technical—it's about clarifying the language describing our problem domain so that we understand exactly what we mean by a Configuration Item (CI) and how it might relate to a Service, in other words how data is related to process. And this is something we need to put together independent of the systems or technology— because it's going to be your road map that helps you determine what exactly the output is going to be in the process definition.

 

How can business gain and maintain the control of their process, in case of change in process due to change in business goals. One technique used for many years is an “entity relationship model” or “E-R Model” and for the entity relationship the other terms used in the business area is said as “Conceptual Model”. The conceptual model can be defined using domain model as well.

 

Conceptual model is needed for Business Stakeholder, Planning and to start top-down modeling to do model driven architecture (MDA).

 

For Business stakeholder: Conceptual model is ideal for the business stakeholders discussion as the model deals with more abstract without uncovering on detailed attributes of an entity. It is presented by covering all the technical specification like type of data, length of data etc.

 

For Planning: During the process definition stage, we don’t required details about data but we need to define the overall data which is specific to business area.

 

To start top-down modeling: In the model driven approach, it is necessary that we have conceptual model so as to transform the entities and attributes identified in this stage are transformed to logical (Architect Perspective – what column) and physical (Engineer Perspective – what column) models.

 

In the next blog, let us see how entity relationship helps in uncovering the dependency between the activities of process.

 

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Kannan Rangarajan is a Principal Architect at iCMG, having in-depth knowledge in Enterprise Architecture. He has around 16+ years of experience, of which 11+ years in providing solutions. He is an expert in solving enterprise problems at different levels like Strategy, Process, System and Technology. He has worked in various domains like Banking(Retail & Corporate), Airlines(Flight Operations, Service Delivery), Travel (Loyalty, CRM and Leisure), Online Media(Sports) etc.... 


 


The experience breadth covers formulating  Business Process improvements, Application Portfolio management and delivering IT services.


 


The delivery aspect involves accountability for design and development of products and solutions. His knowledge area covers in depth in Zachman Framework for Enterprise Architecture, Data architecture, Data warehouse, Master Data Management etc....

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