G****ovTech Data Practice
The Data Practice drives innovation and sets best practices for the effective and responsible use of data across the Whole-of-Government (WOG). We work at the intersection of data engineering, AI, privacy, and governance - developing standards, platforms, and tools that enable agencies to build high-quality data products and unlock the value of data for public good.
Today, most organisations still struggle with data that is fragmented, inconsistent, and hard to use, alongside AI that is powerful but brittle without strong data foundations, and privacy policies that are difficult to operationalise. We are changing that at a national scale.
We are reimagining data engineering itself through AI for Data Engineering (AIDE), which introduces self-improving data pipelines that detect, fix, and optimise themselves, AI-assisted data modelling and quality management at scale, and semantic, context-aware data layers that make data instantly usable for AI. Underpinned by standardised, AI-native architectures, this ensures every agency can build strong foundations from day one.
At the same time, a Trusted Data Nation only works if data can be used without compromising privacy or security. We operationalise Privacy-Enhancing Technologies (PETs) into real capabilities, including federated computing to unlock insights without moving data, differential privacy and synthetic data to enable safe sharing, and trusted execution environments to compute on sensitive data securely. Alongside this, we build the golden paths for Singapore by creating reference architectures, reusable components, standard data platforms, and engineering playbooks that scale quality across government.