Persona: Analyst (Explore, Validate, Explain)
This page is a practical workflow for analysts using MCP Engine to understand semantic models, validate numbers, and explain “why is this KPI doing that?”.
What you typically want
- Quickly understand model structure and key business measures.
- Validate totals and breakouts with small DAX queries.
- Compare security roles (when needed) without exposing row-level data.
- Generate documentation and query suites for stakeholders.
Recommended workflow (15–30 minutes)
Connect intentionally and confirm context
"List available models/datasets and ask me which one to connect to (don't auto-select). Confirm Desktop vs Service." For the full connection workflow, see Connecting and Context.
Get oriented (model tour)
“Summarize the model: main tables, relationships, key measures, calc groups, and roles.”“Highlight likely fact tables and date tables.”Find what you care about
“Search for ‘margin’ across names/descriptions; then show the top 10 relevant measures with short explanations.”“If needed, search expressions and list the measures/calc items that implement the logic.”Validate numbers (small, safe queries)
“Run a validation query for[Total Sales]by month for the last 12 months. Return only aggregates.”“Return top 20 products by[Gross Margin %]for last 30 days. Keep it small.”Explain results (with evidence)
“Explain[Gross Margin %]and run a tiny query that shows numerator/denominator side-by-side for top 10 products.”
Prompt patterns that work well for analysts
Common analyst use cases (copy/paste)
“What measure drives this visual?”
“Find the measure behind ‘Gross Margin’ (table + name). Explain it in plain English and list dependencies.”“Are the totals correct?”
“Validate[Total Sales] last 30 days vs prior 30 days. Return only aggregates and explain any unusual deltas.”
“Is security causing differences?”
“Test this aggregate query across roles A/B/C and summarize differences (no raw rows).”Locked-down environments
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