Executive dashboard
A C-level opens the phone and understands in 30 seconds how the company is doing.
03 / BI-DASHBOARD
Big Data
BI DashboardsBig Data — Clear insights, not slides packed with charts.
Clear insights, not slides packed with charts.
We design dashboards that people actually use: metrics defined with the business, reusable semantic models, decision-focused design. Power BI, Tableau, Looker, Metabase, Superset.
<2s
Target load time
1 only
Definition per metric
+70%
Typical adoption post-redesign
§ A
Overview
The problem with dashboards isn't technology: it's that they often answer questions no one asked. We start from the decisions the business has to make and design backwards, defining metrics and their context with care.
We work with any modern BI tool and curate the semantic layer (dbt metrics, Cube, LookML) so metrics stay consistent across dashboards, applications and APIs.
§ B
What's included
- Metric design workshop with business sponsors
- Semantic layer modelling
- Dashboard wireframes and UX
- Implementation (Power BI, Tableau, Looker, Metabase, Superset)
- Performance tuning on large volumes
- Embedded analytics in your applications
- Training and change management
§ C
Deliverables
What you get at the end — or along the way — of an engagement on BI Dashboards.
- D/01Metric catalog with definition and formula
- D/02Reusable semantic model
- D/03Set of operational and executive dashboards
- D/04Design system for future dashboards
- D/05Training material
§ D
Use cases
Operations command centre
Operations rooms with live dashboards for production, logistics, customer service.
Embedded analytics
Dashboards embedded in your SaaS apps to deliver value to customers.
Self-service analytics
Business users build their own analyses on certified models.
§ E
Our process
01
Discovery
Decisions to support, audience, frequency.
02
Metric design
Formal KPI definition with the business.
03
Build
Semantic layer and dashboard implementation.
04
Adopt
Roll-out, training, initial hand-holding.
05
Iterate
Improvement based on feedback and usage analytics.
§ F
Technologies
Microsoft Power BITableau · LookerMetabase · Apache Supersetdbt Semantic Layer · CubeThoughtSpot · Sigma
Indicative stack. We adapt choices to your context, internal skills and existing constraints.
§ G
Frequently asked questions
Q/01Which BI tool is best?+
It depends. Power BI for Microsoft ecosystems, Tableau for advanced visualisations, Metabase/Superset for open-source, Looker for a strong semantic model.
Q/02Can I avoid vendor lock-in?+
Yes. Keeping business logic in the semantic layer (dbt, Cube) makes dashboards interchangeable.
Q/03How much does a dashboard cost?+
A well-built executive dashboard takes 5–15 days between design, build and validation.
Next step
Let's talk about bi dashboards.
A 30-minute call to understand your context and whether we can really help. No commitment.