BI & Dashboards
One definition per metric. No more duelling spreadsheets.
Governed semantic layers and self-service reporting where revenue means the same thing in every dashboard — so meetings are spent on decisions rather than on reconciling whose number is right.
The Meeting That Starts With Whose Number Is Right
Almost every organisation past a certain size has the same meeting. Two people bring conflicting figures for the same metric, the first twenty minutes go on reconciling them, and the actual decision gets deferred. The cause is rarely bad analysis — it is that no single definition was ever agreed and encoded.
A semantic layer fixes this by making metric definitions code: version-controlled, peer-reviewed, and applied consistently wherever the metric appears. Changing the definition of active customer becomes a reviewed pull request rather than an undocumented tweak in one analyst's saved query.
With that foundation, self-service becomes safe. Business users can answer their own questions without an analyst intermediary, because the guardrails are in the model rather than in one person's head.
Service Inclusions
Governed Semantic Layer
Metric definitions in version control, reviewed like application code, applied identically everywhere.
Genuine Self-Service
Business users answer their own questions within a governed model, so analysts work on analysis rather than ad-hoc report requests.
Drill-Through to Source
Every figure traceable from dashboard to source row, so anyone questioning a number can check it themselves.
Row-Level Security
Access controls in the model, so regional teams see their own data without maintaining separate reports.
Anomaly Alerting
Threshold and anomaly alerts pushed to Slack or email, so the numbers reach people rather than waiting to be checked.
Performance Tuning
Aggregate tables and caching so dashboards load in seconds and warehouse costs stay predictable.
A Process Built for Clarity
No black boxes. No surprise invoices. Every project at Mornis Global follows a disciplined four-phase process designed to reduce risk and maximise value at every stage.
Metric Audit
Catalogue every metric in current use and document where definitions conflict. This is usually revealing.
Definition Workshops
Facilitated sessions to agree one definition per metric, with an owner recorded for each.
Semantic Model
Definitions implemented as version-controlled code with tests confirming they behave as agreed.
Core Dashboards
Executive and team dashboards built on the governed model, prioritised by decision frequency.
Enablement
Training so business users can self-serve confidently within the model.
Governance Process
A documented process for proposing and reviewing metric changes, so governance survives us leaving.
The Tech Stack
We select technologies based on performance, scalability, and long-term maintainability, not trends.
dbt Semantic Layer
Specialized implementation of dbt Semantic Layer in the Metrics space.
Looker
Specialized implementation of Looker in the BI Platform space.
Power BI
Specialized implementation of Power BI in the BI Platform space.
Tableau
Specialized implementation of Tableau in the BI Platform space.
Metabase
Specialized implementation of Metabase in the BI Platform space.
Snowflake
Specialized implementation of Snowflake in the Warehouse space.
Real-World Impact
GreenEarth
The Challenge
“Board reporting consumed a week of analyst time each month, and three departments maintained conflicting definitions of the same core metrics.”
The Solution
We audited 40+ metrics in active use, ran definition workshops to agree a single version of each, implemented them in a version-controlled semantic layer, and rebuilt reporting on that foundation.
Key Performance Indicators
Common Inquiries
Everything you need to know about our specialized services.
Whose Number Is Right?
If your meetings start by reconciling figures, the problem is governance rather than analysis. Tell us which metrics are contested.