MappingsComing soon
Reconciling fields across sources so datasets can be joined. Not yet available.
Not available yet
Mappings are in development. Nothing described here can be configured today, and the Mappings tab is not yet in the product. This page describes what is planned so you can tell whether it will solve your problem.
The problem it solves
The same customer arrives with a different shape from every system:
| Source | Field | Example |
|---|---|---|
| Orders (MySQL) | billing_email |
ana@example.com |
| CRM Contacts (Elasticsearch) | Email Address |
Ana@Example.com |
| Leads (CSV import) | contact email |
ana@example.com |
A mapping will resolve all three to one logical field — email — with a normalisation rule, so
data from unrelated sources can be filtered and charted together.
What is planned
- Logical fields named once per team, with source fields pointed at them.
- Normalisation rules — trim, lowercase, digits-only, date parsing — applied on match.
- Unmatched records surfaced as a count rather than silently dropped, so a failed match is visible instead of quietly shrinking a total.
- Suggestions proposing likely matches from field names, types, and sampled values, with a person accepting each one.
Until then
Reconcile fields upstream — a view in your database, a computed column in a sheet, or consistent naming at the source. A dataset that already speaks one vocabulary needs no mapping.
What this affects elsewhere
Anything that joins across sources depends on mappings and is therefore also not yet available. Charts, dashboards, and investigations all work normally within a single dataset.