Dashboards people make decisions with
Not “one more report” but a screen for a specific decision: what question it answers, who looks at it and what to do when a number moves. Below is an example architecture — change the sources and goals.
Sketch your data architecture
Pick sources and goals — the diagram appears on the right straight away: sources, pipeline, warehouse, BI and outputs.
- CRM → ETL · ELT
- ERP · 1C → ETL · ELT
- Billing → ETL · ELT
- ETL · ELT → Data quality checks
- Data quality checks → Data Warehouse
- Data Warehouse → Data marts
- Data marts → BI layer · metrics
- BI layer · metrics → Dashboards, Scheduled reports
- Dashboards
- Scheduled reports
SOURCES CRM · ERP · 1C · Billing PIPELINE 3 connectors · Scheduled / incremental loads · Deduplication · validation · reference data STORAGE Data Warehouse (PostgreSQL or ClickHouse by volume) · Data marts per department OUTPUTS Dashboards · Scheduled reports
This is a preliminary outline. The architecture may change once we look at your sources.
Metrics first, charts second
We define the metrics and their owners and agree on one formula for revenue and conversion — and only then draw.
- A metric catalogue with definitions
- Drill-down from company to manager
- Role-based access
A dashboard that speaks up
Thresholds and alerts: a manager learns about a deviation from a notification, not at next week’s meeting.
Let’s look at your data
Five questions and you get a preliminary data architecture and a first step. Or just write to us.
Preliminary data architecture