Case Study: Cleanaway achieves unified data insights and AI-led efficiency with Databricks

Ensuring a smarter and cleaner Australia

Cleanaway, Australia’s leading waste and recycling services provider, needed a better way to unify data from its many operational systems and reduce the manual effort required to analyze information. As its collection, sorting, logistics, fleet, and customer data became increasingly scattered across disparate sources, Cleanaway turned to Databricks and the Databricks Data Intelligence Platform to support its data transformation journey and create a single, reliable view of key business metrics.

With Databricks, Cleanaway implemented a lakehouse architecture to consolidate siloed data into a single source of truth and improve analytics and machine learning across use cases like demand forecasting, ESG reporting, and predictive maintenance. The result was more streamlined data management, more dependable insights, and better support for faster, data-driven decisions aimed at improving operational efficiency, profitability, and sustainability.

Cleanaway

Maayan Dermer

Head of Data, Analytics & Al/ML