Measures vs metrics (calculations)
Both measures and metrics are calculations. The difference is complexity.
Measure — one unit of calculation
A measure is a single unit of calculation: something you can count, average, min, or max directly from data without composing multiple named calculations in a formula.
Analogy: In (V = I x R), current ((I)) and resistance ((R)) are like measures—individual measured quantities.
Examples in Analytics:
Headcount as count distinct of employee ID
Average salary
Max / min of a field
Measures can include filters (for example, count only records that are Active or On Leave).
Metric — formula over measures
A metric takes one or more measures and combines them in a formula to produce a number.
Analogy: Voltage ((V)) is like a metric—it needs (I) and (R) in an equation.
Example: Attrition rate = total exits ÷ entire population (× 100 for a percentage). In the formula editor you reference measures (syntax such as $MeasureName tells the system to resolve that name from Measures).
Dimensions (groupings)
A dimension is how you group or bucket records so similar things sit together.
Everyday analogy: Sorting pens by color, or closet outfits by color, or store shelves by size. The dimension is the attribute you group by (color, size, age band, gender, ethnicity, department).
In Analytics, dimensions are typically expressed as case logic that tags each employee (or record) with a bucket label—for example, age bands 0–20, 20–30, and so on from date of birth.
You do not have to group a story. You can show average salary overall, or average salary by age band, gender, ethnicity, or department.
How they combine in a story
A story asks:
Show me this calculation (measure or metric)
Show it this way (KPI, pie, bar, line, table)
Optionally group by this dimension (or hierarchy)
Optionally filter the underlying records
As of this time, and optionally compare to another period
Calculation (measure or metric) + optional Dimension / Hierarchy + optional Filter + Time / Compare to → Story visual
Related building blocks
Concept | When you need it |
Complex derived columns (for example, years of service across intermittent leaves) before measures/metrics | |
Nested drill paths (company → department → cost center, or country → state → city) |