Bind a report to your live sources

These are handoff integrations, not replacements for the source tool. Each one delivers some of three outcomes:

• Editable data for Rahoto tables, charts, calculations and variants.
• A permissioned run reference that keeps the source link and run lineage.
• A stored document kept in Rahoto-controlled artifact storage as a reference.

Mode

Connect and test your Mode workspace, choose a report, and run it from Rahoto. Save the result rows as a governed dataset for editable tables and charts, or import the completed run's PDF. Rahoto keeps the source report and run lineage. A live Mode visual is not available, because Mode has no supported snapshot-link API for it.

Hex

Connect and test Hex, choose a published project, run it, and save its permissioned run reference with project and run lineage. Reports use that reference without copying credentials or short-lived links into the document. Result tables and image or document exports are not available, because Hex's Project Runs API does not expose them.

Funnel

Funnel keeps collecting and scheduling the export. Rahoto guides you to a supported destination (Push API, Amazon S3, BigQuery, Snowflake, Redshift or Google Sheets), which you then connect as a data source. Funnel moves structured data only; it does not import visuals or finished reports.

Power BI, Tableau and Looker

Connect Power BI with a Microsoft Entra service principal, Tableau with a personal access token, or Looker with API client credentials. Power BI imports a report as a stored PDF. Tableau imports editable view data or a stored view PDF. Looker imports a Look as editable data or renders a dashboard into a stored PDF. Provider credentials never enter report content.

Sigma and ThoughtSpot

Connect Sigma with OAuth API client credentials to import a workbook's completed PDF export. Connect ThoughtSpot with a scoped REST API token to import an Answer as editable data or a Liveboard as a stored PDF. Rahoto keeps the source and run lineage. Editable Sigma workbook-element data is not available yet.

Supermetrics

Supermetrics keeps collecting marketing data and running its scheduled transfer. Connect the same Amazon S3, BigQuery, Snowflake, Redshift or Google Sheets destination to Rahoto with separate read-only credentials, and Rahoto refreshes after the transfer window.

When you connect a source, Rahoto discovers its schema and creates a dataset, the reusable handle you bind report elements to. From there:

1. Add a data source and enter its credentials.
2. Let Rahoto discover the available tables and fields.
3. Bind a table, chart or saved value to a field, or to an expression or aggregate over several fields.

Once an element is bound, its numbers come from the dataset every time the report runs. See Design reports for binding inside the editor, and Publish & schedule for how a run becomes a delivered document.

Datasets refresh on a schedule, so a bound report reflects current data without a manual re-export. Set the cadence that fits the source; the same schedule can feed a report that publishes and delivers itself (see Publish & schedule).

Source schemas move: a column is renamed, a field dropped, a type changed. When a dataset's schema drifts from what your report expects, Rahoto raises a schema-drift notice instead of silently breaking a binding.

The mapping wizard then re-binds the affected placeholders in three steps: pick the source, map each field, review and save. Nothing publishes on a broken binding until you confirm the mapping.

No live connection required. Upload a CSV, Excel (XLSX), JSON or Parquet file and bind to it like any other dataset. It is the quickest way to build a first report or work from a one-off extract.

A report is a designed document, not an unbounded data grid, so two limits keep the editor responsive. Both are shown in the app rather than failing silently:

• A table renders up to 50,000 rows in the editor; past that you see a "showing the first 50,000 of N" banner.
• Single-shot full-content export is capped at 10,000 rows; larger tables export through the page-split path instead.

For very large tables, narrow at the source: filter, aggregate or select only the columns you need with a SQL WHERE clause or a dataflow step. A focused dataset is faster to design against and makes a cleaner document.