This is a minor feature release which resolves the following issues:
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Australia’s healthcare sector is swimming in data, but struggling to staff it. From digitised records to AI-assisted diagnostics, the systems are there. What’s missing is a steady pipeline of people trained to manage, govern and actually use that data safely. Right now, most clinical and operational staff aren’t taught the
The frameworks that govern clinical information, HL7, ICD-10, SNOMED, matter. But they’re only one part of what makes data usable, safe, and trustworthy. Compliance doesn’t cover everything. Especially when your organisation’s data is spread across dozens of systems that fall outside the usual health informatics scope. Staffing tools, research portals,
The healthcare sector is built on standards; HL7. SNOMED. ICD-10. They’re the scaffolding of clinical data systems. But what about everything else?
Data teams are hired to solve problems, build models, and unlock insights. But in most organisations, that’s not where they’re spending their time. Too often, they’re stuck cleaning up messes, chasing down missing files, reconciling inconsistent sources, and piecing together context that should have been documented right from the start.
Metadata tools have become table stakes for organisations that care about data governance. But here’s the problem: most of them only work on the systems you already know about. And if your metadata strategy only sees what’s already documented, you’re not managing your data, you’re managing an illusion of it.
At first glance, it’s easy to assume you’ve got a handle on your organisation’s data landscape. You know what’s in your CRM. You know what’s flowing through your data warehouse. You’ve got dashboards full of KPIs. But what about the LinkedIn engagement metrics sitting in your marketing team’s spreadsheets? Or
