Design governed data products from your business knowledge. Not from your database schemas.
A Snowflake Native App that inverts how data products are built. You define your domain and processes. The platform designs the structure. Then you bring your data in.
Select your domain. Define your process. Provide context.
The platform generates entity models and process maps from your domain and process knowledge. Works for any domain, any process. No pre-built entity libraries. If you can't find your domain, add it via configuration.
- Maintenance
- Procurement
- Production
- Inventory
- Finance
- HR
- Safety
- + Any custom domain
Group entities into data products. Define governance at the business level.
Access controls, validation rules, and lineage map to business concepts, not table names. Governance is inherent: defined before any source data is connected.
Open the visual designer. Connect your source systems.
A designer canvas where your team maps source data to business-defined data products. Data profiling shows what is in each table. Business naming ensures the output speaks your language, not the database's.
Output: Facts and Dimensions using your business language.
Visual designer shipped and live.
Map source tables and columns to your data product fields in one view. The canvas shows profiling, lineage, and business names side by side, so your team connects data without leaving the designer.
Metrics and semantic views from your data products.
Governed metrics defined once. Semantic views built from those metrics. Every output tagged with process knowledge, enhancing the context available to analysts and AI agents.
One metric, one answer, every team.
Patent pending on process-aware automatic generation.
Governed data products meet Snowflake Intelligence.
Snowflake Intelligence answers questions in natural language. But the quality of the answer depends entirely on the quality of what it can see. Column names like AFIH_NUM or F0911_MCU tell it nothing.
The Data Product Studio gives Snowflake Intelligence something worth reading: business-named semantic views, governed metrics with process context, and lineage that traces back to the domain. When the AI looks at your data, it sees Maintenance Orders, Cost Centres, and OEE — not table codes.
Better structure in. Better answers out.
Walk through the visual designer with your process.
20 minutes. Your domain. Your language in the output.