NCompas builds enterprise BI platforms, certified metric stores, financial reporting automation, and AI-native dashboard intelligence on Power BI, Microsoft Fabric, Tableau, and Looker — so your leadership team acts on facts, not assumptions.
Why NCompas
Enterprise BI fails at adoption, not technology. We design for the human and the business first — with the technical architecture that makes it scale.
Every BI engagement starts with a metric certification process — defining each KPI once, assigning a business owner, and locking the calculation logic into the semantic layer. No more "which revenue figure are we using?" moments in the boardroom.
Deep Power BI and Microsoft Fabric expertise — certified architects, DAX optimisation, semantic model design, and Power BI Premium capacity management. We also deploy Tableau and Looker where they're the right fit. No vendor bias.
Dashboards that load under 2 seconds for 10,000 concurrent users. We design aggregation tables, DirectQuery optimisation, Premium capacity right-sizing, and incremental refresh strategies — so Monday morning doesn't crash your BI platform.
A BI platform that isn't used is infrastructure spend, not business investment. Every engagement includes an adoption programme — phased rollout, champions network, training sessions, and usage monitoring — so the platform becomes part of the daily workflow.
Row-level security, data masking, sensitivity labels, content certification, and deployment pipelines from dev to production — BI governance that satisfies IT security, satisfies legal, and still lets business users move fast.
Natural language querying, AI-generated insight narratives, and anomaly detection are configured from the start — not treated as future roadmap. Your business users ask questions in English; the BI platform surfaces the answer, not a blank report builder.
Six BI solution types
Business intelligence isn't one thing. We deliver all six layers — from board-level scorecards to real-time operations to AI narratives — on a single governed platform.
Automated financial statements, management accounts, variance analysis, and multi-entity consolidations that replace manual Excel processes. Month-end close accelerated from weeks to days. Full audit trail from source ledger to board report.
Board-level dashboards and executive scorecards that give leadership a single, trusted view of the business — revenue, margin, headcount, pipeline, risk, and operational health — updated in real time and accessible from any device.
Real-time dashboards for operations teams — call centres, manufacturing floors, fulfilment centres, and field services — that display live metrics so managers intervene in minutes, not the next day after a batch report.
Automated financial statements, management accounts, variance analysis, and multi-entity consolidations that replace manual Excel processes. Month-end close accelerated from weeks to days. Full audit trail from source ledger to board report.
Governed self-service BI environments where business users explore their own data without raising IT tickets — enabled by a certified semantic layer, row-level security, and curated workspaces that prevent metric chaos.
Analytics built directly into your application, customer portal, or SaaS product — giving end users the insights they need without leaving your platform. Multi-tenant security, white-labelled dashboards, and usage analytics.
BI that explains itself — AI-generated narrative summaries, natural language querying, automated anomaly detection with root-cause explanation, and smart alerts that tell decision-makers what changed, why, and what to do about it.
Platforms & tools we deploy
How we work
Six phases that deliver a governed, adopted, and AI-ready BI platform — with a production dashboard every sprint and adoption metrics tracked from day one.
Inventory every existing report, dashboard, and data source. Map which reports drive decisions and which generate noise. Document the metric definitions that matter to each stakeholder — before we write a single DAX expression.
Define every KPI with business owner, calculation logic, refresh SLA, and row-level security requirement. Build the semantic model or metric store that makes every dashboard consistent — automatically.
Validate that the underlying data layer is fit for BI — completeness, quality, and freshness. Identify gaps that need data engineering fixes before BI can be trusted. BI built on bad data accelerates bad decisions.
Sprint-based dashboard delivery with business-owner review at the end of every two weeks. Iterative feedback loops. Every dashboard signed off against the metric definitions agreed in step two before it goes to users.
Row-level security, content certification, sensitivity labels, deployment pipelines, and capacity management configured before production launch. IT, security, and compliance teams sign off before business users go live.
Phased rollout with champions programme, training workshops, and usage telemetry from day one. Monthly BI health reviews — which reports are used, which are ignored, which need redesigning. Quarterly platform upgrades.
Industry results
Four industries, four BI transformations. Every metric is from a production deployment — boards and CFOs rely on these numbers daily.
The Challenge
Global bank with 14 business units each producing separate management accounts in Excel. Month-end close taking 22 days. No consolidated view of P&L by segment, geography, or product. CFO reading 11 different spreadsheets before every board meeting.
What We Built
Unified financial BI platform on Microsoft Fabric with automated multi-entity consolidation, Power BI board packs generated in minutes, and a single management accounts model covering all 14 units. Month-end now runs automatically; the CFO reviews a single dashboard.
Global bank with 14 business units each producing separate management accounts in Excel. Month-end close taking 22 days. No consolidated view of P&L by segment, geography, or product. CFO reading 11 different spreadsheets before every board meeting.
Hospital trust with 28 departments each producing their own operational reports. Bed occupancy, staff ratios, and wait times reported 24 hours late. No single view of whole-trust operational health for the executive team.
Global manufacturer with 8 factories across 4 countries. OEE, yield, and downtime reported manually in Excel by each plant. No cross-factory benchmarking. Supply chain disruptions identified only after they hit the P&L.
220 stores with store managers receiving weekly Excel packs. No daily trading view. Regional performance comparisons impossible. Head office analytics team spending 60% of time preparing reports, 40% actually analysing.
of Power BI dashboards are never viewed after their first week — built without a defined business owner, clear decision use case, or adoption plan. Governance prevents this from day one.
reduction in ad-hoc IT report requests within 90 days of deploying a properly governed self-service BI environment — the most measurable ROI signal from any BI programme.
average value of analyst time recovered annually at a 500-person organisation when manual report preparation is replaced with automated BI — that's productive hours returned to analysis and action.
the year AI-generated narrative reports will be standard in 60% of enterprise BI platforms — organisations without a conversational BI roadmap will face a rebuild, not an upgrade (Gartner).
Insights from real-world engineering, cloud, and AI leaders - helping you make better decisions, faster.
We're putting the finishing touches on this. Check back soon for in-depth insights.
Start with a free BI Audit — we'll review your current dashboards, identify metric inconsistencies, map your self-service gaps, and show you what a properly governed enterprise BI platform would look like for your organisation.