DASHBOARDS EXECUTIVES ACTUALLY USE

NUUN Digital — a business intelligence agency for dashboards that executives actually use.

Quick Answer: NUUN Digital builds BI programs from semantic-layer design through dashboard delivery — on Looker, Tableau, Power BI, Metabase, or Snowflake-native BI. Dashboards that answer the CEO's question, not the dashboard builder's. Every dashboard has a named owner, a refresh SLA, and a decision it's built to support.

WHAT WE DELIVER

BI strategy and roadmap. What gets measured, for whom, at what cadence.
Semantic-layer design. dbt, LookML, or equivalent — one source of truth for metrics.
Dashboard build. Executive, operational, and analytical dashboards.
Self-service enablement. Training and governance for in-house analyst teams.
Governance framework. Metric definitions, ownership, approval process, and deprecation.
Data-integration pipelines. ETL/ELT work to feed the BI layer (in partnership with Data Management).

HOW WE DO IT

Understand the decision map. What decisions, at what cadence, by whom.
Design the semantic layer. Metric definitions before visualizations.
Build and validate. Dashboards reviewed against decision requirements and data integrity.
Deploy with training. Users can navigate, interpret, and request extensions.
Govern and iterate. Monthly reviews of dashboard usage; retire what's not used.

PLATFORMS WE BUILD ON

Looker · Tableau · Power BI · Metabase · Preset · Snowflake native · Mode · ThoughtSpot · Custom-built on Snowflake, BigQuery, or Databricks. Platform selection based on scale, data architecture, and user base.

SELECTED WORK

Enterprise client — BI rebuild with semantic layer → [X]% reduction in conflicting metrics across departments. Read case →
SaaS client — Exec dashboard consolidation from [X] dashboards to [Y] → decision cycle time reduced. Read case →

SOURCES & FURTHER READING

Data & Analytics practice
Data Management practice
Marketing analytics and attribution
dbt — https://www.getdbt.com/
Looker — https://cloud.google.com/looker/

Frequently asked.

Which BI tool should I use?

Depends on user base, scale, and ecosystem. Looker for engineering-led orgs with dbt; Tableau for power users and complex analytics; Power BI for Microsoft-centric enterprises; Metabase for simpler scopes. We recommend based on your environment, not our relationships.

How do you solve the "every team has their own number" problem?

Semantic layer with governed metric definitions. Every metric has one owner, one definition, and one source of truth. Teams can still cut and filter; they can't redefine.

Do dashboards actually get used?

Only when designed for decisions. We track dashboard usage post-launch; unused dashboards are diagnosed (wrong metric, wrong cadence, wrong audience) or retired.

Can you migrate from Tableau to Looker (or vice versa)?

Yes. Migration work includes semantic-layer rebuild, dashboard re-authoring, training, and parallel-run before cutover. We minimize "rebuild exactly what you had" when the migration is an opportunity to improve.

How much should we invest in BI?

Depends on scale and decision volume. Typical enterprise BI teams run 0.5–1% of revenue; high-data-dependent industries (financial services, retail) run higher. ROI comes from decision quality, not dashboard count.