Consulting · Business Intelligence
From source to metric, every step traceable.
We design data architectures, build ETL pipelines, model data and make it usable in dashboards. Every figure can be traced back to its source.
Where the data is created
Connected through APIs and files
Load and cleanse
Star schema
Metrics
Example architecture with sample values. The right platform depends on your systems and your team.
Focus areas
Four disciplines, one continuous pipeline.
A dashboard is only as good as what lies beneath it. That is why we advise on the whole pipeline, not just the surface.
A platform that fits you
We design data platforms around your systems, your data volume and your team.
- Inventory of your source systems
- Lakehouse, data warehouse or both
- Roles, access rights and budget
Data that arrives reliably
We build load pipelines that run without anyone having to step in, and that tell you when something is wrong.
- Incremental loads
- Data quality rules and checks
- Documented lineage for every column
A model everyone understands
We model facts and dimensions so that business teams can ask their own questions and the same metric means the same thing everywhere.
- Kimball star schema
- Consistent metric definitions
- History tracking where it is needed
Dashboards that support decisions
We design reports that answer a question rather than show every number.
- Metric workshops with your business teams
- Dashboards and self-service reports
- Training, so your team can keep building on its own
Data modelling
One fact at the centre, its context all around.
Star schema
The measurable events sit at the centre; around them are the dimensions you filter and group by. This keeps reports fast and metrics unambiguous.
Platforms
Modern tools, used where they fit.
We work with the widely used cloud and BI platforms and recommend the one that fits your existing systems.
Power BI
Reports and dashboards on a strong data model, closely integrated with Microsoft 365 and Teams.
a fit if you already work with Microsoft
Tableau
Visual analysis with great freedom of presentation, strong on exploratory questions.
a fit for teams that want to explore freely
Microsoft Fabric
Data integration, lakehouse, warehouse and Power BI on one shared foundation with OneLake.
a fit if you want everything on one platform
Amazon QuickSight
Dashboards directly in AWS, billed by usage and embeddable in your own applications.
a fit if your data lives in AWS
AWS
S3 as a data lake, Glue for loading, Redshift as a data warehouse. Building blocks that grow with your needs.
a fit for flexible, scalable pipelines
Snowflake
A data warehouse with independently scalable compute and simple data sharing between partners.
a fit for changing workloads and data sharing
We are not tied to any vendor. Product names are trademarks of their respective owners.
Live data
See for yourself what data can become.
On our Analytics page we analyse real, openly published data – live, if you choose. Six reports on electricity, climate, money, the world, the Earth and attention: every figure comes with its source, and every step from query to metric is visible.
Filter, compare, try things out – that is how we work on your projects, too.
Industries
Every industry asks its own questions.
We have already led projects in telecommunications, real estate, SaaS and automotive; these industries are marked ‘Project experience’. Choose an example. The data trail and the data model above then show how the answer is built.
How we work
Start small, grow steadily.
Assessment
We look at your sources, your existing reports and the key questions your business teams ask.
Architecture
We propose a target architecture, including platform, budget and roles.
Pilot
We build one pipeline from source to dashboard for a specific question.
Expansion and handover
We extend the solution step by step and train your team so it can keep building on its own.
Let’s talk
Tell us which question your data should answer.
A first conversation clarifies where your data lives, what is missing and where we should start.