Tata Power has announced a strategic collaboration with Databricks to deploy a unified, enterprise-wide data and artificial intelligence platform. The initiative is aimed at accelerating digital transformation, enhancing operational efficiency, and supporting the company’s long-term commitment to sustainable energy growth.
As the energy sector undergoes rapid change, Tata Power is strengthening its digital backbone to support expanding renewable capacity, smart grid adoption, and a growing customer-centric business model. The new platform is designed to integrate data across business units, enabling faster insights, improved forecasting, and more efficient decision-making across the organization.
The deployment will help Tata Power enhance grid intelligence, optimize power generation and distribution, and streamline customer-facing operations such as billing and service delivery. It will also support improved renewable energy forecasting and operational performance across solar manufacturing and rooftop solutions, reinforcing the company’s clean energy ambitions.
At the core of this initiative is a modern data architecture capable of handling large-scale, real-time data processing. By consolidating previously fragmented systems, Tata Power aims to eliminate data silos and create a single, reliable source of truth. This integrated approach will allow teams across the organization to access consistent insights, improving collaboration and accelerating innovation.
A key feature of the platform is the integration of AI-driven tools, including Databricks’ conversational analytics capability, which enables employees to interact with enterprise data using natural language. This functionality simplifies access to insights, empowering teams to generate reports, dashboards, and analytics more efficiently, without requiring deep technical expertise.
Dr. Praveer Sinha, CEO and Managing Director of Tata Power, stated that the collaboration represents a significant step in building a digitally enabled energy ecosystem. He emphasized that leveraging advanced data and AI capabilities will help the company improve operational agility, enhance customer experience, and support the transition to cleaner energy systems.
Nick Eayrs, Vice President of Field Engineering for Asia Pacific and Japan at Databricks, highlighted the growing role of data and AI in transforming the energy sector. He noted that the collaboration will enable Tata Power to develop more resilient, intelligent energy systems while driving innovation at scale.
In the coming months, Tata Power plans to expand the platform’s capabilities to support self-service analytics and broader adoption of AI-driven decision-making across the organization. The company will also establish a strong data infrastructure supported by its internal Centre of Excellence and a network of strategic partners.
Tata Power, part of the Tata Group, stands among India’s leading integrated energy companies, with operations spanning power generation, transmission, distribution, trading, renewable energy, energy storage, and solar manufacturing. With a total installed and managed capacity exceeding 16 GW, the company continues to expand its clean energy portfolio at a rapid pace. Focused on sustainable growth, Tata Power is actively advancing toward its goal of achieving net-zero carbon emissions before 2045 while delivering reliable and future-ready energy solutions across the value chain.
Databricks is a global leader in data and artificial intelligence solutions, enabling organizations to build, scale, and manage advanced analytics and AI-driven applications. Trusted by over 20,000 enterprises worldwide—including leading brands such as adidas, AT&T, Bayer, Mastercard, Rivian, and Unilever—the company supports more than 60% of Fortune 500 firms. Headquartered in San Francisco and operating through over 30 offices globally, Databricks provides a unified platform that brings together data engineering, analytics, and AI capabilities, helping organizations drive innovation and make data-driven decisions at scale.
