Governed self-service BI and reporting structure
Autonomous business teams on Power BI, Qlik, Tableau or your BI tool, without losing trust in the figures
Learn moreData documentation and certification
Certified once, two uses: documented, defined and approved data serves both your business teams’ autonomy and your AI projects
In brief
- Indicative duration
- 4 to 10 weeks per domain
- Format
- Fixed price
- Method step
- Step 2, Certify
Who it is for
- Companies whose KPIs have several definitions
- Teams preparing self-service BI or conversational BI
- Data teams answering the same questions over and over
The problem we solve
Everyone calculates revenue their own way, tables are described nowhere, and AI has no idea what a column means
How we work
- Data catalogue and data dictionary on the priority domains
- KPI catalogue: definition, calculation rule, source and owner, approved by the data owners
- Semantic models and certified datasets in your BI tool, Power BI, Qlik, Tableau or another
- A certification cycle and trust indicators visible to users
What you get
- A data catalogue and a data dictionary
- An approved KPI catalogue
- Documented semantic models
- Certified datasets, flagged with a badge
- A certification and update process
Tools
Microsoft Purview, Collibra, DataGalaxy, Power BI, Qlik, Tableau, SAP Analytics Cloud
Frequently asked questions
What is a semantic model?
The layer that turns your technical tables into business concepts: customers, orders, margin. It holds the definitions and calculation rules, once, for every report
Why does documentation matter for AI?
An AI that answers in natural language relies on the descriptions and definitions of your data. Without them, its answers change from one question to the next
Let’s talk about your data
30 minutes to review your context and identify the first useful project
Related services
AI, automation and conversational BI
Use cases chosen for their value, that hold up in production
Learn more