Data Analytics
Decisions backed by numbers, not instinct
We work with our clients and do a deep analysis of their business using various BI tools. We prepare the possible outcomes of different decisions so leaders can choose with confidence instead of guessing.
- Reporting cycle
- From days to minutes
- Single source of truth
- Across every function
What this practice actually does for you.
We work with our clients and do a deep analysis of their business using various BI tools, then build the reporting layer that makes the next decision obvious, including what each option is likely to cost or return.
The work usually starts before the dashboard: agreeing definitions, connecting sources, and designing a warehouse that reports can be trusted against. Only then does visualisation add value.
We hand over documentation and train your analysts, so the dashboards keep evolving without a consultant in the room.
What we deliver
- Executive and operational dashboards
- Data warehouse and pipeline design
- Power BI, Tableau, and Looker delivery
- KPI frameworks and definition governance
- Self-service analytics enablement
Toolkit
- Power BI
- Tableau
- Looker Studio
- BigQuery
- dbt
- SQL Server
The data analytics delivery path.
Four stages, each with a defined output you review before the next one starts.
- 01
KPI definition
Agree what each metric means, who owns it, and which system is authoritative: the step that stops two reports disagreeing later.
- 02
Pipeline & model
Connect ERP, CRM, spreadsheets, and operational systems into a modelled warehouse built for reporting performance.
- 03
Dashboard delivery
Executive and operational views in Power BI, Tableau, or Looker, designed around the decisions each audience makes.
- 04
Enablement
Training, documentation, and a governance model so your own team can extend reporting safely.
Where clients start with this service.
Executive performance cockpit
One board-level view of revenue, margin, cash, and operations, refreshed automatically instead of assembled by hand.
Sales and margin analysis
Profitability by product, channel, and customer, so commercial teams can see where discounting is quietly eating margin.
Operational monitoring
Daily dashboards for production, logistics, or service levels, with thresholds and alerts on the metrics that matter.
Data Analytics: questions we get asked.
Not always. For a single source and modest volumes we can report directly. Once several systems are involved, a modelled warehouse is what keeps reports fast and consistent.
Ready to scope your data analytics project?
Tell us what the process looks like today and we will come back with an approach, a timeline, and an honest view of the effort involved.