Board & Snowflake
A practical architecture for connecting Snowflake’s AI Data Cloud with Board
Snowflake helps organizations bring data, analytics, machine learning, and AI together in a governed environment. Board connects those assets to the plans, scenarios, approvals, and decisions that guide business action.
Explore how the two platforms can support a governed path from enterprise data to business plans and outcomes.
Turn trusted data into decisions teams can act on
Organizations are building data products and applying AI to more business questions. But a forecast, model output, or analytics dashboard is only useful when teams can bring it into the decisions they need to make.
That takes more than data access. Teams need shared business definitions, planning assumptions, constraints, scenario analysis, ownership, and a way to review and approve actions.
This guide explains how Snowflake and Board can work together across that journey: Snowflake manages and serves trusted data and selected AI or ML outputs; Board gives business teams the context and planning tools to evaluate options and coordinate next steps.
What the architecture helps you address
The guide explores how to connect data and decision processes while giving each platform a clear role.
With Snowflake, organizations can ingest, transform, govern, and analyze enterprise data, and develop selected machine learning and AI workloads. With Board, they can use that trusted information in planning models, run scenarios, manage workflows, and govern decisions.
The architecture is designed to help organizations:
- Make curated Snowflake data products available to planning teams
- Apply business definitions, assumptions, and planning rules
- Compare scenarios and understand trade-offs
- Coordinate tasks, ownership, and approvals
- Keep permissions, versions, and audit trails in view
- Feed approved plans, actuals, and outcomes back through controlled integrations
From Snowflake data products to business plans
The guide follows a path from operational data to coordinated action:
Enterprise systems → Snowflake data and AI pipeline → Governed data products → Board planning and decision workflows → Business execution and outcomes
It also outlines an example data pipeline, showing how data can be ingested and transformed in Snowflake, made available to Board for analytics and planning, and exported back through a separately configured integration when needed.
From Enterprise Data to Enterprise Decisions
What You’ll Learn
See how enterprise data, Snowflake’s governed data products, and selected AI or ML outputs can connect with Board’s Contextual Decision Layer.
Understand where data engineering, governance, analytics, and selected AI workloads fit, and where business semantics, planning models, scenarios, and decision workflows fit.
Review an example flow using Snowflake ingestion and transformation capabilities, curated tables and views, Board’s connection to Snowflake, and a controlled export path for Board data and feedback.
Explore recommendations for using curated data products, keeping business planning logic deterministic, selecting supported interfaces, and managing writeback through an approved integration.
See how governed data and AI outputs can inform FP&A, financial close and reporting, merchandise planning, supply chain planning, and other enterprise planning solutions.
Recommended for:
CIOs
Chief Data Officers
Chief AI Officers
Enterprise Architects
Data Platform Leaders
Analytics Leaders
Digital Transformation Leaders
Enterprise Planning Leaders
From Enterprise Data to Enterprise Decisions
What You’ll Learn
See how enterprise data, Snowflake’s governed data products, and selected AI or ML outputs can connect with Board’s Contextual Decision Layer.
Understand where data engineering, governance, analytics, and selected AI workloads fit, and where business semantics, planning models, scenarios, and decision workflows fit.
Review an example flow using Snowflake ingestion and transformation capabilities, curated tables and views, Board’s connection to Snowflake, and a controlled export path for Board data and feedback.
Explore recommendations for using curated data products, keeping business planning logic deterministic, selecting supported interfaces, and managing writeback through an approved integration.
See how governed data and AI outputs can inform FP&A, financial close and reporting, merchandise planning, supply chain planning, and other enterprise planning solutions.
Recommended for:
CIOs
Chief Data Officers
Chief AI Officers
Enterprise Architects
Data Platform Leaders
Analytics Leaders
Digital Transformation Leaders
Enterprise Planning Leaders
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