Facing rapid data growth and escalating complexity across multiple Azure data services, Indra Renewable Technologies transitioned to Databricks’ unified platform. This strategic consolidation improved cloud cost-efficiency, simplified data pipelines, and accelerated operational insights for their expanding EV charging network.
- Consolidated multiple Azure services into one governed Databricks platform
- Simplified data pipelines with medallion architecture reduce operational complexity
- Automated BI dashboards and natural language access streamline decision-making
Infrastructure signal
Indra faced escalating operational complexity and cloud costs stemming from a diverse data ecosystem composed of Cosmos DB, Synapse, Azure Data Lake Storage, Azure Functions, and Power BI. Each system was independently scaled and maintained, leading to duplicated logic and fragmented data management.
Migrating to a single Databricks environment allowed Indra to unify their data estate into a governed platform featuring Delta Lake and Unity Catalog. This consolidation reduced cloud sprawl by eliminating redundant Azure Functions and disparate pipelines, putting version-controlled, governed datasets at the core of daily operations and lowering infrastructure maintenance overhead.
Developer impact
By adopting a medallion architecture on Databricks, Indra streamlined their data workflows from raw ingestion (bronze) through transformation (silver) to business-ready outputs (gold). This approach replaced multiple legacy pipelines with a single, reusable, and easier-to-maintain pipeline that services several client use cases on a daily basis.
Developers benefited from standard tooling and a stabilized environment, shifting focus from firefighting infrastructure issues to enhancing data value. The integration of automated AI and BI dashboards also reduces manual report generation and licensing constraints, freeing the team to innovate rather than maintain manual processes.
What teams should watch
Business and operations teams will see a significant boost from the new self-service analytics capability powered by governed gold datasets and hosted in a serverless SQL warehouse. They can access up-to-date KPIs through automated dashboards with embedded conversational AI, enabling faster and more accurate decision-making without reliance on data engineers.
Data governance and platform teams should monitor the transition to platform-wide standardization via Unity Catalog, ensuring consistent data policies across multiple workloads. Observability improvements embedded in Databricks allow improved visibility into data lineage and pipeline health, key for long-term reliability and scalability as Indra’s EV charging network continues to grow.