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data model peer review
Key factors to consider when peer-reviewing a data model:
- Ensure primary and foreign keys are set up correctly to maintain data integrity.
- Validate that relationships have the correct cardinality (one-to-many, many-to-one) and direction.
- Verify adherence to best practices like star schema (fact and dimension tables).
- Columns should have clear, meaningful names that align with business terminology.
- Confirm that unnecessary columns or tables are removed to minimize data load.
These factors help ensure the model is robust, performant, and aligned with both business and technical requirements.
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Cheers,
Kedar
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Hi Kedar_Pande ,
who (business or data engineering team) will tell developers which column should be used to join between two tables , example lead and opportunity tables can be joined by using opportunityid which is foreign key available in lead table). as per my understanding it should be someone from business side
Yes, you’re correct: identifying which columns should be used for joins typically requires input from the business side or data engineering team, as they have a deeper understanding of the data’s context and relationships.
So, while developers handle the implementation, the decision about which columns to join usually rests with the business or data engineering teams.
