Tata Play Fiber has announced its collaboration with IBM to build a next-generation, artificial intelligence (AI)-ready enterprise data lakehouse using IBM watsonx. The new platform will unify 25 disparate data sources into a single, scalable environment to enable advanced analytics, strengthen customer retention, and unlock new cross-sell and upsell opportunities.
Built on IBM watsonx, Tata Play Fiber’s new data lakehouse will optimise and scale AI workloads while consolidating structured and semi-structured data into a trusted, unified foundation for enterprise-wide analytics and informed decision-making.
Commenting on the collaboration, chief executive officer, Tata Play Fiber, said, “Building a robust information system is central to Tata Play Fiber’s digital transformation journey. As we scale our footprint in a dynamic broadband market, we need deeper, faster insights into our customers and operations. IBM’s watsonx platform provides us with a secure, scalable environment that will enable us to strengthen retention, unlock new revenue opportunities, and deliver differentiated experiences.”
Meanwhile, vice president, IT, Tata Play Fiber, said, “Navigating today’s data complexity requires more than just consolidation, it demands intelligence. By unifying 25 data sources into a single, enterprise-wide architecture, we are enabling real‑time visibility across the organisation. We are empowering teams from call center agents to field service engineers with contextual insights that enhance operational responsiveness and elevate customer experience.”
In addition, vice president, technology, IBM India and South Asia, said, “Telecom and broadband providers are undergoing rapid transformation while balancing cost pressures and rising customer expectations. Our collaboration with Tata Play Fiber demonstrates how a hybrid, AI-enabled data architecture can help enterprises modernise their data estates and build a future-ready foundation for AI.”
Through this collaboration with IBM, Tata Play Fiber is shifting from fragmented reporting and manual processes to data-driven decision-making at scale. Apart from enhancing regional demand forecasting, the evolving architecture will incorporate network and additional operational datasets to drive deeper analytics across business and operations in the future.
