See BiAnalyzia turn raw data into governed decisions.
This demo walks through the full journey on anonymized healthcare data — connect a source, map it to the canonical model, run a governed pipeline, and watch KPIs land on an executive dashboard. Seven steps, seven decisions you can make tomorrow.
A complete data-to-decision walk-through on real (anonymized) healthcare data. Every screen is the actual product UI — not a video, not a slideshow.
How AI-assisted mapping, governed pipelines, and deterministic KPIs eliminate the trust problems that quietly kill most analytics initiatives.
About 8 minutes to walk through the journey, plus an interactive panel below if you want to try the workbench yourself. No login, no card, no commitment.
From a raw CSV to an executive decision.
Every step shows the actual screen, the business value, and the problem it removes from your week.
Tenant dashboard
A live overview of connected sources, last pipeline runs, KPI health, and quality scorecards across the tenant.
Executives get a single page that answers 'Is our analytics stack healthy right now?' without chasing engineers.
Eliminates the weekly status meeting and the spreadsheet someone updates by hand every Friday.
Connect a source
Choose a connector (Postgres, MySQL, REST, CSV), drop in tenant-scoped credentials, and run a test-first connection.
New data sources are wired in by an analyst — not a six-week IT ticket — and the credential vault keeps security teams happy.
Removes the friction of standing up a new data feed and the security risk of unmanaged credentials.
Map to the canonical model
A side-by-side workbench: source columns on the left, canonical fields on the right, mapping curves between them.
The same canonical model is used everywhere, so 'readmission rate' means the same thing to every team across every tenant.
Stops the endless 'what does this column mean?' debates that derail every analytics project.
AI suggestion + evidence
Claude proposes a mapping with confidence scores, sample values, and the rationale for each suggestion.
Analysts move 5–10× faster on first-time mapping, and every AI suggestion is auditable — never a black box.
Compresses weeks of column-by-column source analysis into hours, with full transparency for compliance.
Run the pipeline
Approved mappings compile into an ETL run. Watch live row counts, durations, and quality outcomes per stage.
Every load is observable and resumable, so failed runs do not become lost weekends.
Replaces the 'cron job that nobody understands' with a fully audited, replayable pipeline.
Inspect KPIs and drill down
KPI cards with sparklines and comparison bars; click any KPI to drill from the chart down to the source rows.
Decision-makers stop arguing about whose number is right — every chart traces back to an auditable SQL view.
Ends the 'three reports, three different totals' problem that quietly destroys trust in analytics.
Executive weekly digest
A one-page weekly summary: highlights, watchlist, recommended actions, and links into the dashboards behind each.
Leadership gets context, not just numbers — a curated narrative that turns analytics into decisions.
Closes the loop between data and action that most BI tools never bridge.
Built for the people who own the numbers.
BiAnalyzia is opinionated about who benefits and how. Here is what each role gets out of the demo.
- Chief Data OfficerOne governed model, one source of truth, one audit trail across every tenant.
- Analytics LeadOnboard new datasets in days instead of months, with AI doing the grunt work.
- Compliance OfficerHIPAA / FERPA-aware controls, audit log on every change, exportable evidence.
- Operations DirectorResumable pipelines, observable runs, no more lost weekends recovering jobs.
- Executive LeadershipA weekly digest with highlights, watchlist, and recommended actions.
What changes in the first 30 days.
Try the workbench yourself.
Tab through a real mapping workbench, pipeline run, and KPI board — all rendered from a canonical encounter model.
| Source column | Target field | Confidence | Status |
|---|---|---|---|
| patient_ssn | patient.identifier | 98% | approved |
| dob | patient.birth_date | 99% | approved |
| adm_dt | encounter.admission_ts | 94% | approved |
| dsch_dt | encounter.discharge_ts | 94% | approved |
| los_days | encounter.length_of_stay | 88% | approved |
| prmry_dx | encounter.primary_diagnosis | 91% | approved |
| discharge_status | encounter.discharge_disposition | 76% | draft |
Ready to run this on your own data?
Start the free pilot — same stack, your data, in under an hour.