Create a report
Build a new custom report in the Report Builder using templates, the five-step query builder, or SQL mode — then save it to Your Reports.
Use the Report Builder to create custom reports from your institution’s data. Reports are saved under OrgHub → Statistics Center → Your Reports. Where University statistics produces schema-driven exports for external bodies, the Report Builder gives you a flexible query model: pick a data source, join related entities, select columns, apply filters, optionally group and aggregate, then run and export results on demand.
This is the starting point for institutional reporting use cases such as student directories, cohort enrollment overviews, program intake rosters, pass/fail summaries, grade distributions, and any ad hoc list your registrar or faculty office needs — without writing a one-off SQL script outside Fuxam.
Why it matters
Universities constantly need lists and summaries that no fixed regulatory schema covers: who enrolled in which cohort this term, which students match a program intake criteria, how memberships changed after a curriculum update, what the pass rate looks like by module. Spreadsheets copied from multiple systems go stale quickly and are hard to audit.
Saved reports in Your Reports solve that by encoding the query once. Colleagues with permission can re-run the same report each term, apply required filters for the current period, and export fresh CSV or Excel files. Templates accelerate common patterns so you do not start from a blank canvas every time.
For a question-by-question map of common institutional needs, see the Common reports catalog.
How it fits
| Related area | Relationship |
|---|---|
| Statistics and reports | Overview of the reporting model and access |
| Common reports catalog | Which questions to build for |
| Edit a report | Adjust a saved report’s configuration |
| Run and export a report | Execute and download results |
| Share a report | Grant view or export access to colleagues |
| My Exams | Exam data available as report entities when joined |
| Course analytics | LMS teaching dashboards — separate from Report Builder data |
Data in custom reports comes from institutional records maintained across OrgHub — users, cohorts, study programs, enrollments, and related entities. Exam grades entered in My Exams can surface in reports when you join the appropriate entities. LMS engagement metrics from course analytics are not part of this builder; use the LMS for teaching-level insight and the Statistics Center for cross-institutional lists.
Key concepts
| Concept | Description |
|---|---|
| Template | A built-in starting configuration (for example, Student directory, Cohort enrollment overview, Program intake roster) |
| Start from scratch | Opens the query builder with no pre-filled configuration |
| Query Builder | Five-step visual builder for data source, joins, columns, filters, and summarization |
| SQL Mode | Write custom SQL directly (requires permission to write custom SQL reports) |
| Preview | Run a sample query during building without saving |
| Required filters | Parameters enforced on the Report run tab before results appear |
How to start a new report
Open OrgHub → Statistics Center → Your Reports.
Select New Report in the toolbar.
On the Templates tab, choose a starting point:
- Pick a built-in template (for example, Student directory, Cohort enrollment overview, or Program intake roster), or
- Select Start from scratch to open the query builder with no pre-filled configuration.
Switch to the Query Builder tab (or SQL Mode if you have permission and prefer to write SQL).
How to choose a data source
In Query Builder mode, the builder walks you through numbered steps. Step 1 — Data source — is where you pick the primary entity for the report (for example, users, cohort memberships, or study program data).
Open the Data source selector.
Search for and select the root entity you want to report on.
Optionally, in step 2 — Join data — connect related entities so their fields become available in later steps.
Steps 2–5 unlock after you select a data source.
Choosing the right grain
| If you need… | Prefer a root entity that yields… |
|---|---|
| One row per person | Users / student directory style sources |
| One row per enrollment membership | Cohort memberships |
| One row per program intake | Program or intake-oriented sources (or the Program intake roster template) |
| One row per exam attempt | Exam or attempt entities joined to users |
| One row per module or cohort summary | Any detailed source, then Summarize with Group by |
Wrong grain is the most common reason a “pass rate” report looks like a student list — or vice versa. Decide the grain before you pick columns.
How filters and groupings shape the answer
Filters and summarization are how one data source serves many institutional questions:
| Technique | Example effect |
|---|---|
| Filter by term / semester | Limits enrollment or exam rows to the current reporting period |
| Filter by study program or cohort | Produces faculty-scoped headcounts instead of whole-institution dumps |
| Required date-range filter | Forces every runner to pick an intake window (common on Program intake roster) |
| Group by module | Turns attempt-level grades into module-level pass rates or averages |
| Group by cohort | Supports grade distribution and average grade per cohort |
| Aggregation (count, average where supported) | Delivers rates, means, and headcounts for leadership |
How to pick columns and filters
In step 3 — Pick columns — select the fields to include in the report output.
In step 4 — Filter — add filter rules to narrow the result set (for example, by cohort, study program, or date range).
Select Preview to run a sample query and confirm the data looks correct before saving.
Select Save, enter a Report name and optional Description, and confirm.
After saving, open the report from Your Reports to run it or continue editing. Step 5 — Summarize — lets you configure grouping and aggregation; see Edit a report for details on grouping.
Institutional reporting use cases
| Use case | Typical approach |
|---|---|
| Term enrollment roster | Template Cohort enrollment overview or data source on cohort memberships; filter by term |
| Program intake list | Template Program intake roster; required date-range filter for intake period |
| Student directory | Template Student directory; optional filters by program or status |
| Pass / fail rates | Start from scratch; join exam or grade entities; filter by term; group by module; count outcomes |
| Grade distribution | Grade fields with Group by grade value or band; count per group |
| Average grade per module / cohort | Summarize with Group by module or cohort; average aggregation where supported |
| Exam attempt statistics | Attempt-level grain; filter by exam / term; count attempts per student or exam |
| Cross-program headcount | Join study program and user or membership entities; summarize with group-by |
| Ad hoc investigation | Build with filters; use Preview heavily before saving; share read-only access |
| National schema submission | Do not use Report Builder — use University statistics |
More detail on each pattern: Common reports catalog.
Best practices
- Name reports clearly with the audience and purpose in mind — for example, “WS2026 Cohort Enrollment — Registrar” — so shared users understand what they are opening.
- Use Preview after every structural change (data source, joins, columns) before saving.
- Configure required filters for reports that must always be scoped to a term or date range; this prevents accidental full-institution exports.
- Document the intended audience in the optional Description field so future editors know why filters were chosen.
- After saving, share the report with Can view for colleagues who only need to run it, and Can export only when downloads are appropriate for their role.
- Prefer summary (grouped) reports for leadership packs; keep student-level detail for roles that genuinely need it.
Common pitfalls
| Pitfall | Avoidance |
|---|---|
| Wrong row grain | Confirm the Data source entity matches the one row per result you expect (user vs membership vs enrollment vs attempt) |
| Missing fields after join | Complete step 2 — Join data — before picking columns that live on related entities |
| Empty results at run time | Check required filters on the Report tab; they must be filled before data appears |
| Over-broad exports | Add filters in step 4 or required filters for term-scoped reports |
| Building a “national statistics” custom report | Use University Statistics for schema compliance; use Report Builder for internal QC only |
FAQ
Should I use Query Builder or SQL Mode?
Use Query Builder for most institutional reports — it guides you through joins and filters visually. Use SQL Mode only if you have permission to write custom SQL reports and need expressiveness the builder does not cover. Validate SQL carefully before saving.
Can I change a report after saving?
Yes. Open it from Your Reports → Actions → Edit. See Edit a report.
How is this different from University Statistics?
University statistics generates country-schema exports for regulatory submission. The Report Builder creates flexible custom reports for internal operational needs.
Where should I look for pass rates and grade distributions?
Build them here with filters and Summarize, following the Common reports catalog. Do not expect LMS course analytics to answer cross-program institutional questions.