Challenge
When our client's base grew from thousands to several hundred thousand records, it became clear that their Power BI platform could not keep up. At the time, generating a single report in Power BI took more than five hours as the platform struggled with increased loads and large, unoptimized data files.
Additionally, key metrics were buried alongside outdated information, overwhelming the system and hindering timely decision-making. Our client was seeking a solid solution to organize its data.
When our client's base grew from thousands to several hundred thousand records, it became clear that their Power BI platform could not keep up. At the time, generating a single report in Power BI took more than five hours as the platform struggled with increased loads and large, unoptimized data files.
Additionally, key metrics were buried alongside outdated information, overwhelming the system and hindering timely decision-making. Our client was seeking a solid solution to organize its data.
Solution
Data Restructuring & Performance Optimization
We restructured oversized datasets by archiving rarely used data and breaking the remaining data into smaller, query-optimized tables. Backend improvements included rewriting queries, applying indexes and partitions, and configuring single-direction relationships to avoid circular dependencies.
Forecasting System Integration
We built a forecasting module using historical data and AutoML models. These models now provide estimates on channel performance, marketing ROI, and profitability by partner type, all within the Power BI interface.
Front-End & UX Enhancements
To improve user experience, we implemented streaming operations, preloaded visuals for dashboards, and removed redundant queries, reducing report loading time to under 10 minutes.
Data Restructuring & Performance Optimization
We restructured oversized datasets by archiving rarely used data and breaking the remaining data into smaller, query-optimized tables. Backend improvements included rewriting queries, applying indexes and partitions, and configuring single-direction relationships to avoid circular dependencies.
Forecasting System Integration
We built a forecasting module using historical data and AutoML models. These models now provide estimates on channel performance, marketing ROI, and profitability by partner type, all within the Power BI interface.
Front-End & UX Enhancements
To improve user experience, we implemented streaming operations, preloaded visuals for dashboards, and removed redundant queries, reducing report loading time to under 10 minutes.
Results
The Power BI transformation drove both immediate and strategic value:
- Report Speed – Reduced generation time from 5 hours to under 10 minutes, empowering daily decision-making across marketing and finance.
- Cost Reduction – Optimized AWS compute and storage costs by minimizing data bloat and inefficient queries.
- Forecasting Capabilities – The forecasting module enables accurate projections of revenue by campaign, channel, and partner, used daily for ROI and budget decisions.
- Improved Scalability – The new data model supports hundreds of thousands of records with zero loss in performance.
- Usability Gains – Analytics and accounting teams now operate in a faster, cleaner, and more stable reporting environment.
The Power BI transformation drove both immediate and strategic value:
- Report Speed – Reduced generation time from 5 hours to under 10 minutes, empowering daily decision-making across marketing and finance.
- Cost Reduction – Optimized AWS compute and storage costs by minimizing data bloat and inefficient queries.
- Forecasting Capabilities – The forecasting module enables accurate projections of revenue by campaign, channel, and partner, used daily for ROI and budget decisions.
- Improved Scalability – The new data model supports hundreds of thousands of records with zero loss in performance.
- Usability Gains – Analytics and accounting teams now operate in a faster, cleaner, and more stable reporting environment.