Precision Focus
Data quality must become national priority, says NITI Aayog
This story was originally published at 14:40 IST on 24 June 2025
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NEW DELHI – With India's digital public infrastructure growing "at breakneck speed", there is a need to ensure data quality keeps pace, a NITI Aayog report released Tuesday said. "As India moves from scale to precision, data quality must become a national priority--on (a) par with infrastructure and platforms," the report said.
In the latest Quarterly Insights Future Front report on "India's Data Imperative: The Pivot Towards Quality", the NITI Aayog said high-quality data can unlock better outcomes and build public trust. "The true test of digital infrastructure is how precisely it represents each individual, not just how many people it onboards. As platforms mature, the focus must shift from expansion to fidelity," as per the report.
Data quality issues crop up as ministries and states develop platforms separately and store data in clashing formats, according to the report. If data quality issues take place at the system design level, it can lead to fake beneficiaries draining budgets.
The NITI Aayog said in the report that high quality data should be accurate, complete, consistent, timely, valid, and unique. It has proposed a self-assessment data quality framework for public institutions to diagnose their data quality standard, identify gaps, and prioritise actions.
The framework has seven dimensions--including data governance and ownership, and quality monitoring--and five levels starting from foundational to institutionalised. Public institutions can use this framework to self-assess the current state on each dimension.
"Institutions can use this framework to move from reactive fixes to a planned, progressive approach to data quality, aligned with their own context and capacity," the NITI Aayog said in its report. "Used together, the scorecard and maturity framework turn firefighting into foresight--exposing blind spots, ordering fixes, and giving every team a shared language for resilient, future-ready data." End
Reported by Shubham Rana
Edited by Rajeev Pai
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