We build executive and departmental dashboards in Power BI, Tableau, Qlik, and Zoho Analytics — connecting your data sources into live intelligence. Including our flagship project for Atlantic LNG, where we created a complete executive BI platform without a single direct database connection.
We don't lead with one tool. We assess your data environment, existing licences, team capability, and budget — and recommend whichever platform actually fits. We've delivered in all four.
Disconnected data, manual reports, dashboards nobody uses — these are the problems we find in every BI engagement.
ERP in one system, CRM in another, finance in spreadsheets, operations in a third database. No unified view. The Atlantic LNG challenge — data spread across multiple systems with no direct connection possible — is the extreme version of what most businesses face in some form.
The CFO's Monday report takes three hours to assemble on Friday. A senior analyst pulling data from multiple sources, formatting in Excel, emailing a static file. Decisions made from data that's already several days old by the time it reaches the meeting.
A Power BI environment was set up two years ago. Six dashboards were created. Three people use it occasionally. The rest of the business still relies on email attachments. The problem is almost never the tool — it's that the dashboards weren't designed around how decisions actually get made.
Finance says revenue is $4.2M. Sales says pipeline converted to $4.4M. Operations says output corresponds to $3.9M. Three departments, three numbers, no canonical definition. Every executive meeting starts with 20 minutes arguing about whose number is right.
A business chose Tableau when Power BI would have been half the price and better integrated with their Microsoft stack. Or chose Power BI when their data complexity required Qlik's associative model. Tool selection matters before implementation begins — and most businesses choose based on the vendor's sales pitch, not an honest assessment.
Revenue visible in the CRM. Margins in the accounting system. Production KPIs in operations. Three systems, three logins, no single executive view. Leadership making decisions from partial pictures because nobody has built the layer that brings it all together.
Data architecture first. Dashboard design second. Adoption tracked as a deliverable.
Before building a single dashboard, we map and connect your data sources — SQL databases, ERP systems, CRMs, Excel files, APIs, cloud platforms. Where direct database connection isn't possible (as with Atlantic LNG), we design alternative ingestion approaches using PowerApps, Excel staging layers, or API connectors to get the data into the BI layer without compromising the source system.
Revenue means the same thing everywhere. Margin is calculated consistently across all departments. Before dashboards are designed, we work with finance and operations leadership to define every key metric — so the numbers are always the same regardless of which dashboard you're looking at. This is the step most BI projects skip and regret.
C-suite and board-level dashboards showing the full business picture — revenue, margin, pipeline, headcount, operational KPIs — in one view updated on schedule. Designed for decision-making, not data display. Every metric on an executive dashboard should drive a decision — metrics that don't are noise. Board pack data assembled automatically from the same model.
Dashboards for each operational audience — sales (pipeline, conversion, rep performance), finance (P&L, cash, budget vs actual), operations (production, capacity, efficiency, raw materials), HR (headcount, leave, performance). Each department sees their data in the format that drives their specific decisions — with access controls ensuring they see only what's appropriate.
Dashboards that push intelligence rather than waiting to be visited. Threshold alerts fire when KPIs breach configured limits. Anomaly detection flags statistical deviations from baseline. Weekly and monthly reports assembled from live data and delivered by email on schedule — the management report arrives before the meeting, not the day after.
A BI implementation is only valuable if people use it. We design dashboards with end users involved — not just stakeholders. Training delivered for both consumers (how to read and act on dashboards) and power users (how to build their own reports in the self-service layer). Adoption tracked as a project KPI at 30, 60, and 90 days post-launch.
Each engagement brought a different data challenge. The Atlantic LNG project is our most distinctive — a complete executive BI platform built without a single direct database connection.
Atlantic LNG is a liquefied natural gas company with operational and financial data spread across multiple systems — different databases, different platforms, different ownership. Direct database access was either technically constrained or operationally restricted. The challenge: build a complete executive dashboard and departmental BI layer from data that couldn't be connected in the conventional way. The solution was pathbreaking — we used Microsoft PowerApps as a structured data collection layer alongside managed Excel data exports, feeding everything into Power BI without touching a single production database.
A restaurant chain — country and company name under NDA — needed a comprehensive BI layer covering every dimension of the business: executive P&L and KPI overview, sales performance by location and period, customer churn analysis, production and kitchen operations metrics, and raw materials usage and waste. Each audience had fundamentally different data requirements and a different way of making decisions from that data. We built the full multi-audience Power BI environment with a shared canonical data model underneath.
For the PrintPlanr print MIS platform and associated CRM solutions, we delivered BI analytics across both Power BI and Zoho Analytics — depending on where the client's data lived and what their existing tool stack looked like. Clients deeply embedded in the Microsoft ecosystem used Power BI. Clients already on Zoho products used Zoho Analytics with native connectors. The underlying data modelling approach was consistent — what changed was the visualisation layer used to surface it.
We have delivered Tableau implementations in the past and have an active Tableau project currently in progress. Tableau is the right choice when visualisation depth and analytical complexity matters more than cost-efficiency — complex calculated fields, nested table calculations, advanced geographic mapping, or large dataset performance where Tableau's in-memory engine outperforms alternatives. We also recommend Tableau for clients already in the Salesforce ecosystem where Tableau CRM (Einstein Analytics) integrates naturally.
A dashboard is the visible layer. The three layers underneath it determine whether the numbers are right, current, and trustworthy.
We've delivered in Power BI, Tableau, Qlik, and Zoho Analytics. When you ask us which tool to use, we give you an honest answer based on your environment — not based on which tool we're currently selling.
Our PowerApps + Excel staging layer approach for Atlantic LNG proved you don't need direct database connectivity to build a complete BI platform. If your environment has similar constraints, we've already solved this problem.
We spend time on canonical metric definitions before building a single visualisation. This is the work most BI projects skip. It's also the reason most BI projects produce numbers that nobody trusts.
Dashboard usage measured at 30, 60, and 90 days. If adoption is low, we investigate why and fix it — whether that's training, redesign, or addressing underlying data quality issues.
ISO 27001. NDA before any data is shared. We audit your data sources before recommending a tool or approach.
Data model agreed first. Tool selected second. Dashboards built third. Adoption measured last.
We map all data sources, assess connectivity, identify quality issues, and define canonical metric definitions with your leadership team.
Data architecture designed. BI tool selected based on your environment — not our preference. Ingestion approach agreed (direct query, staging, or PowerApps where needed).
Dashboards built in staging. Numbers validated against source systems by your team. Every metric agreed before go-live. Alerts and scheduled delivery configured.
Consumer and power user training delivered. Dashboard usage tracked at 30, 60, and 90 days. Low adoption investigated and fixed.
Your business intelligence arrives in a weekly email with a static attachment. By the time you act on it, the situation has moved on. A live executive dashboard means you're always looking at current data — not last week's picture.
Your operational data sits across an ERP, a CRM, spreadsheets, and production systems with no unified view. Even without direct database access — as with Atlantic LNG — we can build a complete intelligence layer from your data.
Monthly close requires three days of manual data assembly. Ad hoc data requests take two days each. Automated BI replaces the manual assembly — finance reviews and approves rather than builds from scratch.