Ontology must already be set up.
Analytics areas
When you open Analytics you typically see four tabs:
Tab | Role |
Manage Analytics | Admin workspace where people create analytics, dashboards, and visuals |
Analytics Groups | Segment employees and control who can see boards |
Automated Exports | Export analytics automatically |
Org Chart | Organization chart |
This documentation covers Manage Analytics and the building blocks used there.
Manage Analytics
Manage Analytics is where admins create the calculations and visuals. The presentation layer is the board: a page where you arrange stories and other widgets (for example, text explanations) so viewers understand the numbers.
Measures / Metrics + Dimensions (+ Data views / Hierarchies) ↓ Stories (visuals) ↓ Boards (presentation) ↓ Groups (who can see a board)
Boards (presentation)
A board is a presentation layout of analytics. You can:
Add stories (the chart or KPI visuals)
Add other widgets such as text for explanations above, below, or beside visuals
Rearrange widgets on the edit page
Assign the board to an Analytics Group so only people in that group can see it
Example: Create a group called Managers, put manager employees in it, and give that group access to a board. Anyone in the group can view that board.
See How to create boards.
Stories (visuals)
A story visualizes a calculation. You choose:
What to calculate — a measure or metric
How to show it — value (KPI), breakdown (pie), segment (bar), trend (line), or data (table)
Whether to group — optional dimension (or hierarchy)
Filters, time period, and comparisons as needed
Temporary board filter
On a board, a temporary filter lets you explore “what if I only looked at this population?” without saving the change.
Example: A board shows active headcount, headcount by employee type, and average salary by age band. Apply a temporary filter for females only; the same stories recalculate for that population. Clearing the session filter returns to the original board view.
Drill down
From a story or board visual, open drill down to see the people (records) behind a number. Use it to validate surprising bands or totals, add columns (for example, date of birth), and optionally download records to recompute averages yourself.