One time
The workshop covers the full arc of data model design — from diagnosing what’s broken in your current state to making specific pattern decisions and building toward AI readiness.
This workshop works best as a cross-functional session. The decisions it covers require both technical depth and business context.
phData has spent more than a decade helping enterprises design and build modern data platforms across Snowflake, dbt, and the full cloud stack. This workshop draws directly from that delivery experience — the patterns that work, the tradeoffs that matter, and the mistakes teams make when they skip this step.
Preferred Partner
2025 Design Partner of the Year
A data modeling workshop is a hands-on working session where teams learn a framework for designing a data model that encodes shared business meaning. phData’s workshop covers diagnosing problems in your current state, choosing modeling patterns, and building toward AI readiness. It runs half a day or a full day, in person or virtually, and ends with a working session on a real domain from your environment.
An AI-ready data model has explicit grain, consistent relationships, and machine-readable meaning, so AI can reason over your data and return consistent answers. It moves metric definitions, entity relationships, and business rules out of dashboards and into the data layer.
A semantic layer is the metadata layer that exposes definitions and metrics to every tool and agent that queries your data. A strong data model feeds it, which keeps reporting and AI answers consistent across tools.
The right pattern depends on what the business needs, not on a default. The workshop compares dimensional, Data Vault, canonical, and wide table patterns, walks through the trade-offs, and applies them to a real domain from your environment
When business definitions live in dashboards and in people’s heads instead of in the data, AI has no consistent meaning to reason on, so answers vary. Every new request also takes longer, and teams spend time validating numbers instead of acting on them. A data model that encodes shared business meaning addresses the root cause.
The workshop works best as a cross-functional session. It is built for Data & Analytics Leaders (CDO, VP of Data, Analytics Director), Data Architects and Engineers, BI and Semantic Layer Owners, and Business Domain Experts who define the use cases AI needs to support.
