This is the substantive data collection phase. You are working with business areas and system owners to identify every in-scope data asset and populate its metadata. Expect this to be an ongoing activity — not a one-off exercise.

Discovery approaches

Most organisations use a combination of methods:

• Self-reporting templates — business areas complete a structured spreadsheet or form for each data asset they hold. Simple and scalable but dependent on engagement.
• Facilitated workshops — working through the template with business areas in a structured session. More time-intensive but produces higher-quality outputs and builds awareness.
• System scanning — using tools (such as Microsoft Purview for organisations on the Azure/M365 stack) to automatically detect data stores, classify content and surface candidate assets. Significantly reduces manual effort for organisations with complex technical environments.
• Interview-based discovery — conversations with subject matter experts, useful for finding data that is not stored in formal systems.

Engaging business areas

Business areas have competing priorities. Make participation as easy as possible:

• Provide a clear, pre-populated template with instructions and a worked example.
• Set realistic deadlines and communicate why this matters for the organisation.
• Offer support — a short call, a drop-in session, or a simple FAQ document.
• Use your senior sponsor to communicate the importance of the exercise to reluctant areas.
• Track engagement using a simple log and follow up promptly on non-responses.

Prompt business areas to think broadly. Data often lives in unexpected places:

• Shared drives (legacy or archived folders)
• Third party or cloud platforms (survey tools, CRMs, application systems)
• Data received from external sources (other agencies, research partners, contractors)
• Physical records being digitised 

Handling new data assets going forward

One of the most important shifts from project to capability thinking is ensuring new data assets are captured at the point of creation, not discovered retrospectively. Consider:

• Requiring a data inventory entry as a standard deliverable for any new ICT project or system implementation.
• Including a data asset notification step in project management templates and governance gates.
• Establishing a simple self-service process for business areas to add new assets between review cycles.

DMAT's Architecture domain assesses whether the organisation has systematic processes for identifying and registering data assets.