Data & Analytics

Business intelligence

Dashboards, semantic layers and self-service reporting that leaders trust and teams adopt.

Überblick

Most organizations do not lack dashboards. They lack dashboards people trust and use. Conflicting numbers, slow reports and unclear definitions send teams back to spreadsheets. We design business intelligence around the decisions it needs to support and the people who make them.

We start by agreeing the metrics that run the business and defining them once in a governed semantic layer, so revenue, margin or customer counts mean the same thing in every report. Dashboards are then designed with users, tested for clarity and performance, and built to draw attention to what needs action rather than displaying everything available.

For self-service, we put guardrails in place: certified datasets, row-level security, naming standards and a clear path for promoting useful analyses into governed reports. We support adoption with training, office hours and usage analytics, and we help retire legacy reports that no longer earn their maintenance cost.

Was Sie erhalten

01Metric catalog with agreed business definitions
02Governed semantic model and certified datasets
03Executive and operational dashboards designed with users
04Self-service framework with security and publishing standards
05Training materials and adoption tracking

Technologien, mit denen wir arbeiten

Microsoft Power BI
Tableau
Looker
Microsoft Fabric
dbt Semantic Layer
Snowflake
Databricks SQL

Wir sind technologieunabhängig: Werkzeuge wählen wir passend zu Ihren Anforderungen und bestehenden Investitionen aus.

Fragen, die wir häufig hören

Can you help us consolidate multiple BI tools?

Yes. We assess usage, cost and capability across your tools, recommend a target state and migrate high-value content while retiring reports that are no longer used.

How do you make sure dashboards actually get used?

We involve users in design, keep each dashboard focused on specific decisions and track usage after launch. Reports with low adoption are reviewed and either improved or retired.