Measure Killer Measure Killer

Identify Excel users of a Power BI semantic model

Use Measure Killer's activity-logs scan to list every Excel user pulling data from a Power BI semantic model — across the last 28 days, with workspace and last-access date.

What you get

A grouped list of every Excel user who has touched one of your Power BI semantic models in the activity log window — with the workspace they connected from, how many activities they triggered, and the last date they accessed the model. The view drills down from model → user → session (e.g. “Refreshing Excel sheet”, “Creating Analyze in Excel file”) so you can see exactly what each user is doing.

Why you need an admin

The data comes from the Power BI / Fabric activity log API, which only returns results to a Fabric Administrator or Power Platform Administrator. The log has a 28-day window — anything older than that is no longer queryable.

Build a history beyond 28 days

Every time you fetch activity logs, Measure Killer automatically appends what it pulled to a local SQLite database on your machine. Run the scan every so often (weekly or monthly works well) and your local store grows past the 28-day API ceiling — you end up with months or years of history that Microsoft no longer returns.

The file lives in Measure Killer’s app data folder, stays on your device, and the next scan transparently merges fresh API results with what’s already there — no extra setup required. (For unattended history collection, the same logic runs on a schedule in MK Automation.)

Run the scan

  1. Open Measure Killer in one of the admin modes: Shared model online, Tenant Analysis, Analysis Services (SSAS / AAS), or MK Automation.
  2. Sign in with a Fabric Admin / Power Platform Admin account.
  3. Click Activity logs in the toolbar.
  4. Pick a Start date and End date (up to 28 days back).
  5. Optionally filter by name — typing excel narrows the tree to Excel-related sessions only.
  6. Click Fetch activity logs.

The tree populates with every semantic model that had activity in the window, expandable into the users who touched it and the sessions they ran.

Read the results

Each leaf row shows:

  • Name — the session label (e.g. “Refreshing Excel sheet”, “Creating Analyze in Excel file”), or a user identity at the next level up.
  • Workspace — where the model lives.
  • # of activities — how many distinct events were logged for that user against that model in the window.
  • Last date accessed (UTC) — when they last connected.
  • Status — a small bar showing the % of days in the window with activity (e.g. 26.7% (8/30) = active on 8 of the 30 days you queried).

Use Export .json to hand the list to a stakeholder, or Copy emails to build a distribution list of the users you’ve just identified.

Common workflows

  • Inventory before a model rewrite — confirm who’s pulling from the model in Excel before you change a column or measure name.
  • Audit shadow BI — find Excel users who bypass the official reports and query the model directly.
  • Right-size the audience — see who’s actually using a model vs. who has permission but doesn’t connect.

What’s next

Identifying the users is half the job. To see which columns and measures each of them is consuming from your model, follow the next step: Find what your Excel users are consuming from your semantic model.