Data Product Workshop
A one-day workshop for data leads, product owners, and cross-functional data teams who want to move from ad hoc data delivery to data products. Business and technical people work through realistic scenarios together and leave with a shared vocabulary, a scoping framework, quality principles, and clear roles. A natural follow-on from the Data Maturity Scan.
Details
Audience
Head of Data / data product leads
Format
1 full day
What is this?
You've made big investments in data, but the business value is still underwhelming or hard to show. The central data team is the bottleneck, business teams wait weeks for data that already exists, and every department has its own version of the truth. Decentralising without shared standards for quality and security creates more problems than it solves.
The Data Product Workshop brings your cross-functional teams together with Dataminded's data product experts for a day of structured learning and hands-on exercises. We work through realistic scenarios together, so your team leaves aligned on vocabulary, framework, and decisions.
How it works
What we cover
- ▸The business case for data products
- ▸Archetypes, ports, and boundaries of a data product
- ▸When to create a new product versus add a port
- ▸Quality principles and data contracts (DAFT UNIVRS)
- ▸Roles across the data product lifecycle
- ▸Semantic models and AI-readiness
What your team practises
- ▸Scope a data product with a shared decision framework
- ▸Apply quality principles and data contracts to a data product
- ▸Assign roles across the data product lifecycle
What you get
- ✓A shared vocabulary across business and technical stakeholders: data products, archetypes (source, aggregate, consumer-aligned), ports, contracts, ownership
- ✓A decision framework you can apply tomorrow: when to add a port, when to create a new product, when to move logic upstream into an aggregate, practiced through four hands-on scenarios
- ✓Ten measurable quality principles for a good data product, data contracts to formalise them, and five defined roles across the lifecycle
- ✓A view of where data products are heading: why connecting LLMs directly to raw data fails, how semantic models bridge that gap, and why your data product foundation is also your AI foundation
Format
| Duration | 1 day |
| Level | Beginner |
