Tata Power builds unified data platform to accelerate grid operations and renewable integration
Tata Power has adopted Databricks to consolidate fragmented data systems across its entire enterprise, targeting near real-time insights for grid management and operational decision-making.
The platform integrates data engineering, analytics, and AI across renewable energy, smart grids, solar manufacturing, and customer-facing operations. It replaces traditional data warehouses with a centralised system designed to handle large volumes of operational data.
Real-time grid intelligence as priority
Tata Power plans to use the platform for intelligent grid management, power planning, renewable energy forecasting, and billing optimisation. The system processes data from edge, operational, and enterprise sources-eliminating silos that previously fragmented decision-making.
As renewable energy sources introduce variability in supply, the ability to act on data in near real time has become critical for grid stability. The unified platform will enable faster, data-driven decisions on energy distribution and grid flexibility.
Tata Power CEO Praveer Sinha said the partnership strengthens the company's digital foundation to support smarter operations and accelerate renewable integration.
Self-service analytics for operations teams
A key feature is Genie, an AI agent that lets employees query enterprise data using natural language. Operations staff can generate insights and dashboards without relying on specialised technical teams.
This "talk-to-data" capability addresses a common bottleneck: operational decisions delayed while waiting for analytics support. Teams can now access insights directly.
The implementation is backed by an internal Centre of Excellence and partner ecosystem to build and scale data capabilities across the organisation.
Shifting from passive to active customer engagement
Tata Power is consolidating customer data across touchpoints to deliver a single-view experience. The platform supports a shift where customers move from passive consumers to active participants managing and optimising their own energy usage.
For operations teams, this means handling more granular, real-time customer data and responding to demand-side signals faster than traditional systems allow.
Learn more about building data foundations for operational excellence with our AI Learning Path for Operations Managers, which covers process optimisation and operational decision-making in data-driven environments.
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