Conceptual Data Model (CDM): A Top-Down Approach

Last updated Feb 9, 2024

In the top-down approach, we commence with a high-level perspective of an organization’s data requirements. This process involves collaborating with business owners, domain experts, and various stakeholders to grasp the business necessities and formulate a conceptual data model.

Subsequently, this model undergoes iterative refinement, transitioning from a conceptual to a logical, and ultimately, to a physical data model. This method is especially advantageous when there’s a comprehensive understanding of the business requisites and objectives.

The conceptual data model represents a structured business perspective of the data necessary for supporting business processes, documenting business events, and tracking pertinent performance metrics. This model’s primary focus is on the data utilized within the business, excluding its processing flow or physical attributes.

Dave Coulter, in a tweet, highlighted:

In an organization of substantial complexity, the presence of a CDM provides an excellent framework to align logical and physical models, independent of source systems. Utilizing dbt and distinct layers such as landing>staging>marts>metrics ensures technical elegance and cleanliness. The real challenge lies in fostering data literacy.

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Discover more about Conceptual, Logical to Physical Data Models

Origin: Tweet, Data Modeling – The Unsung Hero of Data Engineering: Modeling Approaches and Techniques (Part 2) | ssp.sh
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Created 2023-03-23