SQL Server Data Warehouse
The Challenge: Operating across multiple global regions, our company utilizes different ERP systems in each territory, alongside specialized software for specific business functions. This fragmented infrastructure created numerous data silos, making unified reporting and meaningful business insights nearly impossible. Analysts struggled to perform comprehensive sales analysis, purchasing reviews, or cross-regional comparisons without manual data aggregation. The Solution: I architected and developed a centralized SQL Server data warehouse that consolidates data from multiple ERP systems and auxiliary databases into a single source of truth. This unified platform provides clean, consistent datasets for reporting, analysis, and application development across the entire organization. Technical Implementation: • Automated data ingestion using scheduled Python scripts that extract and load data from disparate source systems • Incremental update strategy for large tables to minimize impact on production servers and optimize sync performance • Periodic full synchronization to maintain long-term data consistency and catch any missed incremental changes • T-SQL stored procedures for complex data transformations, business logic implementation, and efficient data manipulation • Dimensional modelling to support analytical queries and enable intuitive reporting structures • Error handling and logging to ensure data quality and facilitate troubleshooting Business Impact: The data warehouse enables real-time reporting across territories, supports data-driven decision making, and eliminates hours of manual data consolidation work previously required for cross-regional analysis. This is an extensive, ongoing project with many moving parts. You'll find related components and specific implementations featured elsewhere in my portfolio.
Back to Portfolio
