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MoSPI held Workshop on Data Harmonisation for Use of Administrative Data in Data Driven Governance

The Ministry of Statistics and Programme Implementation (MoSPI) held a workshop on September 8, 2026, bringing together statistical advisers and chief data officers from across central government. The event focused on improving how administrative data is organized and shared to support better government decision-making and policy design.

What was discussed and launched

The workshop centred on data harmonisation—the practice of making different government datasets compatible and understandable across departments. Senior officials, including the Principal Secretary to the Prime Minister, stressed that reliable, timely and interconnected data is necessary for policies based on evidence rather than assumption.

A new online portal called the Quarterly Progress Report (QPR) on Data Harmonisation was launched during the event. This platform allows all central ministries and departments to report on their progress in cataloguing datasets, preparing metadata, applying common standards and conducting quality checks. The portal includes automated checks and dashboards that show progress across the entire government.

MoSPI highlighted several existing initiatives meant to support this work: the National Master Data System (NMDS 2.0), a Statistical Quality Assurance Framework, common classification systems, data lifecycle guidelines, and a microdata portal. Officials also mentioned national platforms like API Setu, data.gov.in and AI Kosh through which data can be shared.

What this means for you

Better data sharing within government should eventually lead to more informed policies and programmes that serve citizens more effectively. If ministries can access and understand each other’s data through common standards and formats, they can design interventions based on clearer evidence about what works. The workshop’s emphasis on making data “AI-ready” also suggests the government plans to use machine learning and automated analysis to spot patterns and improve service delivery, though such systems depend on data being reliable and properly organized first.

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