The Challenge

The client struggled with a legacy reporting system that was slow, disconnected, and unable to handle the growing volume of IoT sensor data from their manufacturing lines. This resulted in delayed operational visibility and reactive, rather than proactive, maintenance.

The Solution

We designed and implemented a robust Azure Databricks architecture. By building automated Spark pipelines, we ingested and structured streaming IoT data into a Delta Lake, creating a unified, high-performance analytics backend directly connected to Power BI.

Key Results

• Processing millions of records/day reliably
• 80% faster reporting and dashboard load times
• Better operational visibility enabling predictive maintenance

Technologies

The Challenge

The organization was bottlenecked by a legacy ETL architecture and an on-premise data warehouse. Queries took hours to run, scalability was limited, and the system required constant, expensive engineering maintenance to prevent failures.

The Solution

We executed a complete data warehouse modernization by migrating their ecosystem to Snowflake and implementing a Medallion Architecture using Databricks. We standardized their data models and optimized partitioning strategies for analytical workloads.

Key Results

• 60% faster queries for the BI and Data Science teams
• Infinite scalability with decoupled compute and storage
• Significantly lower maintenance and infrastructure costs

Technologies