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Power BI

People analytics is only worth the decision it changes. I build Power BI dashboards that surface workforce anomalies and compliance risks as decisions — using statistical modeling and machine learning — not charts that describe headcount history.

The Workflow — How I Approach It

1

Define the workforce question

Attrition, overtime, compliance exposure — start with the decision, not the visual.

2

Clean the people data

The biggest source of HR analytics error — validate before you visualize.

3

Detect anomalies

Statistical modeling and machine learning surface signals before they become problems.

4

Present as decisions

Surface risks stakeholders can act on — not a dashboard waiting to be interpreted.

My Operating View — The 2 Cents

The best people data in the world is wasted as a bar chart. My 2 cents: start from the workforce question and end at the decision. Anomaly detection on people and operational data converts analytics spend into risk avoided — that’s the standard.

What Worked & What Didn’t

What Worked

  • Surfaced operational anomalies as actionable signals for stakeholders.
  • Decision-first design — every visual had a purpose.

What Didn’t

  • Dashboards that describe headcount history — polished and ignored.
  • Visuals built before the data model — expensive rework.