What Arcwise is
An analytics platform built around one question: why did this metric move. It connects to a warehouse or BI tool, watches for meaningful changes, and produces an explanation that can be traced back to the underlying data and documents.
The emphasis on traceability is deliberate, since an unverifiable summary is not much use in a business review.
What you can do with it
- Detect meaningful metric changes early
- Turn a movement into a decision-ready explanation rather than a chart summary
- Connect Snowflake, BigQuery, Databricks and similar sources
- Pull in business documents and metric definitions as context
- Audit how a conclusion was reached
Who it is for
- Data teams, operations analysts and growth leads
- Logistics and aviation teams tracking operational metrics
- Anyone answering why a number changed more often than they would like
What to watch out for
- It depends on existing data sources and business context, so permissions, data quality and metric definitions need sorting first
- AI explanations shorten the analysis path but the cause still needs confirmation from business and data sides
- One-off spreadsheet formulas or light visualisation do not need this
Pros & cons
✓ What we like
- Focused on explanation, not just charts
- Traceable back to data and documentation
- Connects to major warehouses
- Useful for recurring why-did-this-move work
! What to watch out for
- Requires clean data sources and agreed metric definitions
- Anomaly causes still need human confirmation
FAQ
Is this a spreadsheet assistant?
No. The current focus is metric change detection and decision reporting, better understood as a business analysis platform.
What data sources does it connect to?
Snowflake, BigQuery, Databricks and similar, with the exact scope depending on your environment.
Why the emphasis on traceability?
Because business analysis needs to be auditable, rather than resting on a single unverifiable summary.
Last reviewed: 2026-09-15
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