Design data models for Dynamics 365 solutions
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Table of Content:
- Question 1: Why is data modeling critical in a Dynamics 365 / Dataverse implementation?
- Question 2: Why is table ownership (User/Team vs Organization) important?
- Question 3: What is the impact of relationships on security?
- Question 4: When should field-level security be avoided?
- Question 5: What are alternate keys, and why are they important?
- Question 6: When should calculated and rollup columns be used?
- Question 7: Why is auditing critical in data modeling?
- Question 8: Why should large external data not always be copied into Dataverse?
- Question 9: What role does Export to Azure Data Lake play?
- Question 10: How does data modeling affect user experience?
- Question 11: Why should unused columns be excluded from search?
- Question 12: When should you use choice columns vs lookup tables?
- Question 13: Why is using a single publisher and custom prefix important?
- Question 14: What are column mappings, and why are they useful?
- Question 15: What is the purpose of the Data Model Workshop in Success by Design?
- Question 16: What is an Entity Relationship Diagram (ERD), and why is it important?
- Question 17: What are best practices for designing ERDs in Dynamics 365?
- Question 18: When should you use out-of-the-box tables instead of custom tables?
- Question 19: Why should you avoid re-creating standard tables like Account and Contact?
- Question 20: In which scenarios is it acceptable to not use the Account table?
- Question 21: What risks exist when repurposing system tables?
- Question 22: Why should unnecessary table options be removed during table creation?
- Question 23: Why are N:N relationships discouraged in complex scenarios?
- Question 24: What are bridge tables, and when should they be used?
- Question 25: What is the final responsibility of the solution architect after the workshop?