OneLake Data Catalog in Singapore
The OneLake catalog is the central hub to discover, manage, govern and secure every data item across Fabric. We set it up so your people find the trusted dataset in seconds — and your Copilot and agents ground on endorsed, governed sources rather than the nearest available table.
The OneLake catalog is the single place to discover, govern and secure every data item across Fabric. Set up well, it is what lets your people find trusted data — and your agents ground on endorsed sources instead of whatever they stumble on. Singapore organisations operating across APAC face a specific challenge: the HQ analytics platform works well for Singapore. It doesn't work for the manufacturing plant in Johor or the distribution centre in Jakarta. Regional consolidation — pulling operational data from sites with different ERPs, different data quality levels, and different local reporting requirements — into a single APAC view is the most common project we run for Singapore-based organisations.
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Singapore regulatory data governance
Regional HQ-to-operations consolidation
Multi-country, multi-currency reporting
Local currency engagements available
What we hear from operators
The problems we solve
These aren't hypothetical pain points assembled from industry reports. They're observations from actual plant floors, warehouse ops, and finance desks — written down because they come up in almost every first conversation.
Nobody can find the right dataset
In a growing Fabric estate, the same data exists in five workspaces and nobody knows which is current. So teams rebuild what already exists, and two reports on the same question disagree because they were built on different copies. A catalog with search, tags and descriptions is what turns "does this exist?" from a Slack message into a two-second lookup.
No one knows which number to trust
Without endorsements, every dataset and report looks equally official, so a user picks whichever they find first — often the wrong one. Certification and promotion in the catalog mark the trusted, owned assets clearly, so people and agents use the endorsed source instead of guessing. Trust has to be visible to be useful.
Governance posture is invisible
When you cannot see which items are sensitive, undocumented or over-shared, you cannot fix it — and sensitive data quietly spreads. The catalog's governance view surfaces the posture of the data you own and the actions that improve it, turning governance from an annual audit into an ongoing, visible practice.
Agents and Copilot ground on ungoverned data
The reason AI over your data gives confident wrong answers is often that it grounded on the nearest table rather than the right one. A governed catalog with endorsed sources is what lets Copilot and Fabric Data Agents reason from trusted, classified data — which is why the catalog is a foundation for AI, not just a convenience for humans.
How we work
Our approach
01
Populate and organise the catalog
We make the estate discoverable — tags, clear descriptions, ownership and domains on the items that matter, so search returns the right dataset. A catalog nobody has curated is just a list; the value is in the organisation we put on top of it, focused first on the data people actually need.
02
Govern with endorsements and Purview
We set up certification and promotion so trusted assets are marked, apply Microsoft Purview sensitivity labels and classification, and use the catalog's governance view to drive down undocumented and over-shared items. This is where discovery becomes governance — people find data and know they can trust it.
03
Secure and embed everywhere
We enforce row-level and object-level security so discovery never means over-exposure, and make the catalog work where your people already are — in Teams, Excel and Copilot Studio, and through the public APIs, Fabric CLI and Fabric MCP for developers and agents. Discovery is only useful if it reaches the point of work.
What changes
Outcomes
These are specific, measurable shifts — not benefit statements. Every outcome listed here has been achieved with a client.
Discovery: "does this exist?" → two-second catalog search
Teams find the current, trusted dataset instead of rebuilding it, so duplicated and conflicting assets stop multiplying.
Trust: every asset looks official → endorsed sources clearly marked
Certification and promotion make the owned, trusted assets obvious, so people and agents use the right source by default.
Governance: annual audit → visible, ongoing posture
The governance view surfaces sensitive, undocumented and over-shared items and the actions to fix them, so posture improves continuously.
AI grounding: nearest table → endorsed, governed sources
Copilot and Fabric Data Agents reason from certified, classified data, which is the single biggest lever on whether their answers can be trusted.
Technology stack
Common questions
What buyers ask us
These are questions that come up in almost every first or second conversation. If yours isn't here, it will be in the first call.
What is the OneLake catalog?
The OneLake catalog is the single place in Microsoft Fabric for data professionals and business users to discover, manage, govern and secure the data they can access across OneLake. It has an Explore experience for finding data with search, tags and endorsements, and a Govern experience that shows the governance posture of the data you own and the actions to improve it. It covers the full range of Fabric item types, including reports and dashboards.
Is the OneLake catalog the same as Microsoft Purview?
They are complementary, not the same. The OneLake catalog is the discovery and governance hub inside Fabric for your Fabric data; Microsoft Purview provides broader enterprise data governance, sensitivity labelling and compliance across your whole estate, including sources beyond Fabric. In practice we use the OneLake catalog for in-Fabric discovery, endorsement and posture, and Purview for sensitivity classification and enterprise-wide governance, and connect the two.
How does the catalog help Copilot and AI agents?
AI over your data is only as good as what it grounds on, and the catalog is how you make the trusted sources the ones agents find. Endorsed, well-described, classified items in the catalog let Copilot and Fabric Data Agents reason from certified data rather than the nearest available table — which is the most common cause of confident wrong answers. The catalog is also queryable through public APIs and the Fabric MCP, so agents can discover data programmatically.
What is the difference between certified and promoted endorsements?
Promotion is a lighter endorsement — an owner or contributor marking an item as ready for others to use. Certification is a stronger, controlled endorsement, usually reserved for authoritative assets and granted under a defined process by a smaller group. Using both well means users can see at a glance which assets are the trusted, owned ones and which are simply shared, which is what stops people building on the wrong copy.
How do we keep sensitive data secure while making data discoverable?
Discovery and security are separated in the catalog: people can find that an item exists and who owns it without being able to open data they are not entitled to. We apply row-level and object-level security and Purview sensitivity labels so access is governed, and use the governance view to find and fix over-shared items. Making data discoverable does not mean making it open — it means making the right people able to find and request the right data.
What are the prerequisites to set up the OneLake catalog well?
A Fabric estate with data worth cataloguing and clear ownership of the important domains. The catalog itself is part of Fabric, so there is nothing to install — the work is curation and governance: assigning owners, adding tags and descriptions, setting up the endorsement process, and applying sensitivity. It works best alongside a governed semantic model and, where you are heading toward agents, a Fabric IQ ontology, so discovery, governance and business meaning reinforce each other.
Related services
Further Reading
Practitioner insights on this topic
Other markets
OneLake Data Catalog in other markets
The operational problem rarely changes at the border. The ERP estate, the compliance regime and the reporting cycle do.
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