The 30-minute rule for better BI dashboards
Most enterprise dashboards fail in the first thirty minutes — not of building, but of thinking. The case for treating those first thirty minutes as the most important part of the project.
Insights
Practitioner writing on actuarial work, data engineering, AI and model validation — and the operating layer that ties them together.
Most enterprise dashboards fail in the first thirty minutes — not of building, but of thinking. The case for treating those first thirty minutes as the most important part of the project.
The "data warehouse vs data lake" debate is over. The lakehouse won. A practical orientation for an actuarial or finance leader scoping their next data investment.
As actuarial teams use generative AI for documentation, code, anomaly detection and assumption setting, the validation playbook needs explicit extensions. Four extensions and a structured way to apply them.
The next round of actuarial modernisation is being decided one layer below the modelling engine — in the data engineering layer. The engine matters less than people think. Data flow matters more than people realised.
The biggest unmanaged actuarial risk in most insurers today is no longer in the model. It is in the unversioned spreadsheets that adjust the model's outputs, and the reporting packs that re-aggregate them.
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