About the Snowflake x Sigma QuickStart

Sigma is a natural next step once Snowflake is live. Where Snowflake centralises and governs data, Sigma makes that data immediately usable for business teams through spreadsheet-like, cloud-native analytics that run directly on Snowflake.

This QuickStart positions Sigma as the fastest path from Snowflake to self-service analytics, without data extracts, semantic duplication, or heavy BI engineering.

How this solution works

Stage 1 – Analytics Use Case Alignment (1 week)

You align business questions with Snowflake data that is already available or nearly ready. The focus is on identifying operational and analytical use cases that benefit from real-time access and ad-hoc exploration (finance, ops, product, revenue).

Outcome:
A prioritized list of Sigma-ready use cases mapped to Snowflake schemas and roles.

Stage 2 – Data Readiness & Access Design (1 week)

You validate Snowflake models, role-based access control (RBAC), and cost considerations for interactive analytics. Sigma’s direct-query model means governance and warehouse sizing matter from day one.

Outcome:
A Sigma-ready Snowflake environment with clear warehouse strategy and access patterns.

Stage 3 – Sigma + Snowflake Technical QuickStart (1–2 weeks)

You connect Sigma directly to Snowflake, configure authentication (SSO), map Snowflake roles, and validate performance. Core datasets are exposed without data duplication or extracts.

Outcome:
A live Sigma environment running natively on Snowflake.

Stage 4 – Semantic Layer & Self-Service Analytics (1–2 weeks)

You build Sigma datasets, metrics, and business logic on top of Snowflake tables. End users work in a familiar spreadsheet-like interface, while all calculations execute inside Snowflake.

Outcome:
Governed, reusable metrics with true self-service analytics for business users.

Key outcomes

1. Faster time-to-insight directly on Snowflake

2. No data extracts, no semantic duplication

3. Business-friendly analytics without losing governance

4. Lower BI engineering overhead

5. Immediate Snowflake value realization