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Sigma integration

Sigma on Polar: one governed truth, in your dashboards.

Point Sigma at Polar's semantic layer and every dashboard reads governed, blended metrics, Net Sales, blended CAC, contribution margin, defined once. Polar is a smart warehouse, per-brand Snowflake with 10 attribution models, not a dumb pile of raw tables, so your BI stops re-deriving numbers in SQL and stops drifting from the source.

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Connect Sigma See the setup
Google Sheets → Polar

What you can bring in

Governed metrics
"My dashboards re-derive everything."
Sigma reads Net Sales, CAC and margin defined once in Polar.
defined once
No raw SQL
"Only my data team can build reports."
Governed metrics mean analysts build dashboards without hand-written SQL.
no SQL drift
Blended sources
"My BI can't blend channels."
Polar blends Shopify, Meta, Google and more before Sigma ever reads it.
blended upstream
10 attribution models
"Which attribution does my dashboard use?"
Polar's smart warehouse carries blended attribution, so dashboards inherit it.
attribution built in
One number everywhere
"BI and the app disagree."
Sigma reads the same governed number Polar's app shows.
one truth
Available over MCP
"Can an AI read it too?"
The same governed metrics answer to the Polar MCP, sourced.
MCP-ready

Sigma on a dumb warehouse re-derives everything. On Polar it just reads the truth.

Pointed at a raw warehouse, Sigma makes every team re-write the same SQL and quietly drift from each other. Polar governs the metrics upstream, so Sigma reads one definition, blended and attributed.

Sigma on a raw warehouse

  • Every dashboard re-derives metrics in SQL.
  • Definitions drift between reports and the app.
  • Blending channels is a modelling project.
  • Attribution is whatever each query assumes.

Sigma on Polar

  • Metrics governed once in the semantic layer.
  • One definition, read the same everywhere.
  • Sources blended upstream before Sigma reads.
  • Blended attribution built into the warehouse.
Setup Guide

Point Sigma at Polar.

01 · What you need
Polar

A Polar account with Shopify

A Polar account with Shopify connected. This connector plugs in right next to your stack.

Connect your data →
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A Sigma workspace

Sigma, pointed at your Polar semantic layer or dedicated Snowflake warehouse.

Open Sigma →

Polar's smart warehouse

Polar governs your metrics in a per-brand Snowflake with blended attribution, ready for your BI to read.

02 · Point Sigma at Polar
1

Connect to the warehouse ~5 min

Read Polar's governed layer.
Point Sigma at your Polar semantic layer or dedicated Snowflake warehouse, where metrics are already governed and blended.
2

Read governed metrics automatic

One definition.
Your dashboards read Net Sales, blended CAC, contribution margin as defined once in Polar, no raw SQL, no re-derivation.
3

Stop the drift the payoff

Smart, not dumb, warehouse.
Because Polar is a smart warehouse with 10 attribution models and blended sources, your BI reads the same number Polar's app shows, everywhere.
Get started

Your BI, on one governed truth.

Connect Sigma to Polar's semantic layer, so every dashboard reads the same governed, blended metric.

Book a demo Connect your data ↗
The Gap

The connector is only half of it.

Once your Sigma dashboards are connected to Polar, you can use them wherever you already work. Ask Polar in plain language, pull them live through the Polar MCP, or schedule a snapshot into the report your team reads every morning.
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Sigma

dashboard queries
Polar

Polar

governed, blended metrics

Ask Polar

Polar MCP

Scheduled reports

Featured Use Case

One definition, every dashboard.

One definition, every dashboard

A BI tool is only as trustworthy as the warehouse under it, and a raw warehouse forces every analyst to re-derive Net Sales, CAC and margin in their own SQL, which is how two dashboards end up disagreeing and neither matches the app. Polar is a smart warehouse: a per-brand Snowflake where metrics are governed in a semantic layer, sources are blended, and 10 attribution models are built in. Point Sigma at it and your dashboards read the same governed number Polar's app shows, no re-derivation, no drift, and the same metrics answer to the Polar MCP for whoever prefers to just ask.

What makes it real

Governed upstream. Net Sales, CAC and margin defined once, before Sigma reads them.

Smart warehouse. Per-brand Snowflake with blended sources and 10 attribution models.

Ask Polar, in plain language. “Which attribution does this dashboard use, and does it match the app?” No SQL, no export.

See how the governed layer works
Other Use Cases

Other use cases

Use case 01

Placeholder

Placeholder. The use case skill fills this. (rung: see it)

See the use case › Use case 02

Placeholder

Placeholder. The use case skill fills this. (rung: report it)

See the use case › Use case 03

Placeholder

Placeholder. The use case skill fills this. (rung: analyze it)

See the use case › Use case 04

Placeholder

Placeholder. The use case skill fills this. (rung: decide from it)

See the use case › Use case 05

Placeholder

Placeholder. The use case skill fills this. (rung: act on it)

See the use case ›
Your Prompt Library

Sigma in plain language

A scannable wall of sample prompts for your Sigma data inside Polar. Ask Polar, or Claude with the Polar MCP connected.
See it
Show the governed metrics available to my BI.
List the attribution models Polar exposes.
Show blended CAC as Sigma would read it.
Analyze it
Do my Sigma dashboards match Polar's app numbers?
Which metric definitions differ between reports?
Show contribution margin blended across channels.
Decide from it
Which dashboards should read governed metrics instead of raw SQL?
Where is definition drift costing us trust?
Summarize which numbers changed after governing them.
Get started · connect once · one governed truth

Your BI, on one governed truth.

Point Sigma at Polar's semantic layer, so every dashboard reads the same governed, blended, attributed metric.

Get started by booking a demo Connect your data in Polar
Phase 1 ~5 minConnect to the warehousePoint Sigma at your Polar semantic layer or Snowflake.
Phase 2 automaticRead governed metricsNet Sales, CAC and margin, defined once.
Phase 3 the payoffStop the driftYour BI reads the same number Polar's app shows.