Data Modeling

Purpose: To demonstrate your ability to design a robust data model that supports business requirements and efficient querying.

Step-by-Step Approach

1. Understand the Use Case

   • Gather functional requirements: What questions does the data model need to answer?
   • Clarify business goals and reporting needs.

2. Identify Key Entities and Relationships

   • Define core entities (e.g., users, products, events).
   • Determine relationships (e.g., one-to-many, many-to-many).

3. Choose Data Modeling Approach

   • OLTP Scenarios: Use 3NF (Third Normal Form) to minimize redundancy.
   • OLAP Scenarios: Use star or snowflake schemas for analytical queries.

4. Design the Logical Data Model

   • Create ER diagrams or schema diagrams.
   • Define tables, columns, keys, indexes, and constraints.

5. Handle Specific Modeling Challenges

   • Address slowly changing dimensions (SCD), denormalization needs, and data versioning.
   • Design for schema evolution and future-proofing.

6. Data Integrity and Performance Optimization

   • Apply indexing strategies, partitioning, and materialized views if needed.
   • Ensure data quality through validation rules and constraints.