What are the best practices for data modeling?
Best practices for data modeling include understanding business requirements, using normalization, and ensuring data integrity.
Can you explain normalization in data modeling?
Normalization is the process of organizing data to reduce redundancy and improve data integrity by dividing it into related tables.
What are some common mistakes to avoid in data modeling?
Common mistakes include over-normalization, ignoring business rules, and failing to involve stakeholders in the design process.
How do I choose the right data model for my project?
Choosing the right data model depends on your project's requirements, the complexity of the data, and how it will be accessed.
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