Data Engineering and Business Intelligence

Data Analytics and Business Intelligence

We define the metric, build the pipeline that refreshes it, and put the view where the decision happens.

The business problem

Leaders ask why a number moved and the answer starts with someone exporting three spreadsheets.

Source mapping and a written metric definition
Pipelines into a warehouse or the reporting tool you already pay for
Dashboards for one operating question at a time
Optional models for churn, anomalies, or forecasting when the history supports them

Replace the copied forecast sheet with a refresh and an exception list.

Surface accounts whose usage pattern changed, for a person to review.

These are patterns for scoping a project. They are not case studies and they do not report a client metric.

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