Enterprise Analytics Case Study
Consolidated fragmented transactional systems into a single trusted analytics platform by rebuilding transaction, revenue, and Line-of-Business (LOB) logic at the SQL and semantic-model layers—eliminating double-counting and restoring executive confidence in reported totals.
Business Problem
- Multiple overlapping transactional systems with inconsistent definitions
- Double-counting driven by regional and system-specific logic
- Low executive trust due to conflicting totals and trends
Architecture Pattern
- Source systems preserved in raw form
- Canonical, auditable SQL views enforce business rules
- Power BI semantic model with mutually exclusive measures
- Executive dashboards as the final consumption layer
What I Did
- Designed canonical, versioned SQL views while preserving raw source data
- Standardized transaction, revenue, and reversal logic with regional exceptions
- Centralized transaction-to-LOB mapping with consistent keys and governance
- Built Power BI semantic models with filter-safe, mutually exclusive measures
- Delivered executive dashboards and stabilized dataset performance
SQL & Data Architecture
- Canonical SQL views as the single source of truth
- Auditable fee calculations and reversal handling
- LOB mapping enforced at the data layer
Power BI Semantic Layer
- Mutually exclusive transaction and revenue measures
- LOB-aware DAX switching and filter-safe totals
- Export governance and Remote Desktop performance stabilization
Business Impact
- Established a single source of truth for transactions and revenue
- Eliminated reconciliation disputes and restored executive trust
- Enabled faster decision-making and scalable forecasting foundations