Challenge
A large manufacturing enterprise was running its reporting and analytics stack on licensed Tableau and Power BI seats across multiple departments. As the user base grew, so did the licensing bill - and the limitations became harder to ignore. Dashboards couldn’t be customized beyond what the platforms allowed, embedding reports into internal tools required expensive add-on tiers, and the data team had no control over query performance or caching strategies. The company needed an analytics platform it fully owned - one that could connect to their diverse data landscape and scale without per-seat costs.
Approach
We designed and built a custom analytics and reporting engine to replace the licensed BI tools entirely:
- Interactive dashboard builder - a Grafana-style interface built in React where users create, configure, and share dashboards with drag-and-drop widgets, custom chart types, drill-down navigation, and real-time data refresh
- 20+ data source connectors - integrations spanning production databases (PostgreSQL, MySQL, SQL Server), ERP systems, IoT sensor feeds, spreadsheet imports, REST APIs, and third-party SaaS platforms - unified through a standardized connector framework
- Django backend with Airflow orchestration - Django REST API handling authentication, authorization, and query execution. Apache Airflow manages scheduled data pipelines, ETL jobs, and connector sync workflows across all 20+ sources
- Caching and performance layer - Redis-backed query caching with configurable TTLs per data source, ensuring sub-second dashboard loads even on complex aggregations across millions of rows
- AI and agentic integrations - natural language query interface where users ask questions in plain English and receive generated visualizations. Agentic workflows for anomaly detection, automated report generation, and proactive alerting when KPIs drift outside defined thresholds
- Role-based access and multi-tenancy - department-level data isolation with configurable access controls, allowing each team to manage their own dashboards and data source connections independently
Result
The platform replaced both Tableau and Power BI across the organization, eliminating recurring per-seat licensing costs that had been scaling linearly with headcount. Beyond the cost savings, the engineering team now has full control over the feature roadmap - custom visualizations, embedded analytics in internal tools, and AI-powered insights that would have been impossible or prohibitively expensive on the licensed platforms. The Airflow-driven pipeline architecture ensures data freshness across all 20+ sources, and the Redis caching layer keeps dashboard performance consistently fast regardless of query complexity.