Case Study: Leading Consulting Company improves analytics with Excellarate

Standardized data model helps a consulting company improve their analytics

Leading Consulting Company partnered with Excellarate to address the challenge of building a database-agnostic standard data model that could integrate data from multiple sources. The company was dealing with fragmented data structures across units, limited technical expertise, and privacy-related data availability constraints, which made analytics inconsistent and slowed decision-making.

Excellarate implemented an aggregate data model and a descriptive analytics pipeline, using a configurable, Python-based ETL solution to standardize raw data from sources such as CSV, Hive, PostgreSQL, Redshift, and SQL Server. The result was reusable analytical components, less duplicate development effort, faster setup and data processing, and improved productivity for business users, with a scalable solution that can support future integrations.