Executive Summary
Engineered a complete Business Intelligence ecosystem, automating the flow of data from a transactional source to an analytical Data Warehouse. The project involved building a robust ETL pipeline, architecting a complex Galaxy Schema, and deploying an OLAP Cube for multi-dimensional analysis.
Technical Architecture
ETL Orchestration (SSIS): Developed automated SQL Server Integration Services packages to extract data from the source, apply transformation logic (data cleaning, deduplication, and mapping), and load it into the DWH.
Data Warehousing: Architected a Galaxy/Snowflake Schema with two centralized Fact tables (Fact_Order_Lifecycle and Fact_Orders) and shared dimensions.
Advanced Modeling: Implemented Many-to-Many relationships using Bridge tables to accurately associate books with multiple authors.
OLAP Cube Development (SSAS)
Multi-Measure Groups: Leveraged SQL Server Analysis Services to build a high-performance Cube, enabling cross-functional analysis of the bookstore’s order lifecycle.
Optimization: Configured custom hierarchies (e.g., Year > Month > Day) and optimized attribute relationships to solve data integrity issues like duplicate keys.
Key Technical Skills Demonstrated
ETL Development: SSIS (Data Flow Tasks, Control Flows, Transformations).
Data Modeling: Kimball Methodology, Galaxy/Snowflake Schemas, Surrogate Key management.
Analytical Processing: SSAS Cube design, Dimension Usage optimization, and Metadata management in SQL Server 2025.
