Data Products & Self-Service
Business teams serve themselves with data instead of waiting in the IT queue.
When every new analysis requires an IT ticket, wait times and frustration build up on both sides. With clearly defined data products and self-service access via Power BI or similar tools, business teams can analyze independently without compromising data quality. IT stays the guardian of standards instead of a daily bottleneck.
- Significantly shorter wait time for new analyses.
- Fewer routine requests hitting IT.
- Higher data literacy within business teams.
wait time for new analyses
more self-service users
to first live data products
IT tickets for standard analyses
Calculated from the number and turnaround time of previous IT tickets for standard analyses.
- 01
Needs analysis
We identify recurring analytics needs of business teams.
- 02
Product definition
We shape data into clearly scoped, reusable products.
- 03
Self-service access setup
We provide secure, easy-to-use access.
- 04
Business enablement
We train staff to work independently with the data.
- 05
Operations & evolution
We continuously refine data products based on usage feedback.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
Semantic models
Predefined metrics and dimensions from the semantic layer.
Usage data
Previous access to reports and analyses.
Business requirements
Documented requests and recurring reporting needs.
Governance rules
Access and classification rules from data governance.
Quality metrics
Approval status and quality rating per data product.
User feedback
Feedback on usage and missing content.
Business units
Direct, independent access to relevant data.
IT / BI team
Fewer routine requests, more time for development work.
Data governance
Controlled self-service instead of uncontrolled data copies.
Executive management
Faster, data-driven decisions across the company.
Significantly shorter wait time for new analyses.
Fewer routine requests hitting IT.
Higher data literacy within business teams.
Consistent use of validated data products instead of Excel sprawl.
Faster decision-making in day-to-day business.
With a solid data foundation this use case gets faster, cheaper and far more stable.
An existing semantic layer is the foundation of every data product.
Established governance secures self-service without losing control.
Central data quality builds trust in self-service.
Existing BI infrastructure speeds up delivery of new products.
Data modeling & semantic layer
The semantic layer supplies the building blocks for every data product.
Data governance & permissions
Governance ensures secure self-service instead of data sprawl.
Business intelligence
Data products are used directly in dashboards and reports.
Lakehouse Architecture
A central lakehouse replaces the patchwork of data warehouse, data lake and Excel exports.
Data Integration from ERP & MES
Automatically merge ERP and MES data instead of exporting and reconciling manually.
Streaming & Real-Time Data
Instead of daily batch runs, relevant metrics are available within seconds.