Data warehouse
Dimensional model, ingestion from sources, data quality.
The data layer that connects ERP, CRM, web and operations in a single dashboard. Postgres / ClickHouse / dbt as an open stack.
Without BI there is no data-driven decision: only opinion based on Excel exports. The first step is always the same: your own data warehouse that gathers data from ERP, CRM, web, operations and your sales platform, and models it into a common layer.
On top of that warehouse, two visualisation options: Power BI when the client is in the Microsoft ecosystem, Qlik when deep exploratory analysis is needed. We operate both platforms as partners.
We deliver the platform with a minimum set of standard dashboards (sales, finance, operations) and train the client's team to build the next ones themselves. The goal is independence, not dependency.
Dimensional model, ingestion from sources, data quality.
Pipelines with dbt. Versioned, tested, reproducible.
Standard dashboards (sales, finance, ops) ready to use.
Maintenance, freshness monitoring, SLA.
The operational detail: what we deliver as part of the engagement and what we keep active afterwards.
Your own data warehouse
Postgres or ClickHouse. No lock-in to opaque SaaS.
ETL with dbt
Versioned in git, automated tests.
Power BI for Microsoft
When the client works in M365.
Qlik for exploratory analysis
When you need to cross-reference and discover.
Standard dashboards
Sales, finance, ops. Ready in weeks.
Team training
Independence, not dependency.
BI on top of the ERP is the natural step. BI with governance is what CSRD will require.
It works, but it ends up siloed. A dedicated BI layer crosses ERP, CRM, web and operations.
2–4 weeks with client data on standard dashboards.
Power BI if you live in M365. Qlik for exploratory analysis or multiple sources.