DE302: Database & Data Warehouse Design

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SFIA Reference: DBDS Level 4/5

Data Engineer (Grade 3)

Competency Description

Designs optimised, scalable, and governed data models to support analytics and storage efficiency.

Learning Outcomes

  • Develop star/snowflake schemas in Synapse or similar.
  • Apply indexing, partitioning, and schema evolution.
  • Define data retention, slowly changing dimensions, and history strategies.

Evidence Requirements

Level 4:

  • Created a data model supporting a reporting need with acceptable performance.
  • Implemented history tracking or metadata structures.

Level 5:

  • Standardised data modelling practices across a domain.
  • Led the implementation of schema evolution or retention policy processes.

Suggested Learning Activities

  • Build a fact-dimension model with SCD support.
  • Join a schema governance working group.
  • Analyse and optimise an existing wide table.
  • Publish a modelling reference guide or blog.

Recommended Resources

  • Kimball Group: Dimensional Modelling Techniques
  • KnowHow: Data Mart Structuring Guides
  • Internal Modelling Standards Repository

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