SQL Data Warehouse & Analytics Project

? Objective

To design and implement a robust, scalable, and well-documented SQL Server-based data warehouse that ingests, transforms, and models data from heterogeneous sources (CRM & ERP), enabling downstream analytics and reporting for business stakeholders.

? Specifications

Data Sources:

Two source systems: CRM and ERP, each providing structured CSV files.

Files are loaded directly into the Bronze layer without transformation.

Data Quality:

Cleanse and resolve data quality issues (e.g., nulls, duplicates, inconsistent formats) during Silver layer processing.

Implement data validation rules and logging for auditability.

Integration:

Combine CRM and ERP datasets into a unified, user-friendly dimensional model in the Gold layer.

Apply star schema design with fact and dimension tables for optimized querying.

Scope:

Focus on the latest dataset only—historical versioning is not required.

All ETL processes are batch-driven, with full-load and truncate-insert patterns.

Documentation:

Clear documentation of the data model, including entity relationships, column definitions, and transformation logic.

Schema diagrams and process flowcharts are provided for stakeholder clarity.