Analytics & BI
One definition of every number.
We build semantic layers and dashboards that leadership can rely on. Metrics are defined once, tested, and reused across every report, so meetings are spent on decisions instead of reconciling figures.
Sound familiar?
The problems we solve
Competing versions of the truth
Revenue means three different things in three different reports.
Dashboard sprawl
Hundreds of reports, few of them used, none of them trusted.
Analysts stuck on extracts
Skilled people spending their week copying data into spreadsheets.
Outcomes
What you get
- Consistent KPIs across finance, sales and operations
- Self-service analytics without spreadsheet sprawl
- Faster, better-designed dashboards people actually use
Approach
How we deliver it
- 1
Start from decisions
Identify the decisions each audience makes and the metrics they need.
- 2
Define metrics once
A tested, documented semantic layer shared by every tool.
- 3
Design for use
Dashboards built with users, iterated on real usage data.
Deliverables
What we hand over
Working software, tests and documentation in your repositories and cloud accounts.
Technologies
- Power BI
- Tableau
- Looker
- dbt Semantic Layer
- Microsoft Fabric
- Sigma
- Metrics layer
- Governed metric definitions with tests and documentation.
- Dashboards
- Executive and operational dashboards designed around real decisions.
- BI rationalization
- Retire unused reports and consolidate duplicates.
- Self-service enablement
- Curated datasets and training for analysts across the business.
Use cases
Where this makes a difference
Executive KPI cockpit
A single view of company performance with drill-down to the source.
Sales and pipeline analytics
CRM data joined with finance for accurate forecasts and commission.
Operational dashboards
Near-real-time views for supply chain, service and operations teams.
FAQ
Common questions
Do we have to change BI tools?
Rarely. A shared semantic layer lets different tools show the same numbers.
Can business users build their own reports?
Yes, on curated datasets with governed metrics, which is what makes self-service safe.
Related services
All services →Data Engineering
Reliable batch and streaming pipelines that move data from every source into your platform, tested and observable from day one.
Batch and streaming pipelines you can trust
ETL & Data Integration
Integrate every system and modernize legacy ETL (Informatica, SSIS, DataStage, Talend) into maintainable, cloud-native ELT pipelines.
Modernize ETL to cloud-native ELT
Big Data Migration
Move Hadoop, Teradata, Netezza, Exadata and on-premises warehouses to a cloud lakehouse safely, with parallel runs and zero-surprise cutovers.
Hadoop and legacy warehouses to the cloud
Tell us where your data is today.
A 45-minute conversation with a senior engineer. You leave with an honest view of what to build first, whether or not we work together.