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Connect Rippling workforce data to Sisense to power custom dashboards and embedded analytics for headcount, compensation, and organizational reporting.
We map Rippling's employee data — headcount, tenure, compensation bands, department structure — into Sisense's data models, structuring the feed to support the specific dashboards or embedded analytics use case the client needs.
For companies with both US and Canadian entities, we configure data segmentation by entity and jurisdiction, so cross-border reporting keeps distinct regulatory contexts separate rather than blending them.
We validate the data pipeline and initial dashboards against known headcount and compensation figures before the client relies on Sisense for reporting decisions.
Sisense is used by US mid-market companies wanting to embed workforce analytics into custom dashboards or client-facing products alongside standard HR reporting.
Canadian and cross-border operations: for companies reporting on both US and Canadian headcount, thePeopleStack configures Sisense data models to segment by entity and jurisdiction so cross-border reporting doesn't blend distinct regulatory contexts.
Rippling employee data — headcount, tenure, compensation bands, department structure — can be exported or synced into Sisense's data models to power custom dashboards and embedded analytics.
Yes — Sisense's embedded analytics capability lets companies build workforce dashboards that can be surfaced inside internal tools or client-facing products, distinct from a standalone BI dashboard.
Yes — for companies with both US and Canadian entities, Sisense's data models can be configured to segment headcount and compensation reporting by entity and jurisdiction.
Data refresh frequency depends on how the Rippling-to-Sisense data pipeline is configured; most implementations sync on a daily or near-real-time basis depending on the client's reporting needs.
A standard setup covering data model configuration and initial dashboard build typically takes 5–8 hours, depending on reporting complexity.
