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Good data systems should be boring.

From raw data to trusted dashboards — we build the systems behind better decisions.

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// No sales pitch. No commitment. Just insights.

Built with Microsoft Power BI Microsoft Fabric Azure Databricks
// our work

Real dashboards.
Real results.

Click through to see examples of what we build — clean, trusted, and built on solid foundations.

Dixons — Sales Analysis
Revenue · Trends · Product
Optic Solutions
Sales · Forecast · Categories
KQN — Regional Sales
Countries · Targets · Categories
Hartwell & Co.
Sales · Provinces · Week Day
app.powerbi.com / dixons-sales-analysis
Dixons Sales Analysis Dashboard

Dixons — Sales Analysis

Regional sales breakdown tracking €204M in iDEAL transactions across product categories. Revenue by region, trend over time, and top-performing product lines — all in one view.

  • Power BI
  • DAX Measures
  • Bar Chart
  • KPI Cards
app.powerbi.com / optic-solutions-overview
Optic Solutions Marketing Impact Dashboard

Optic Solutions — Marketing Impact

Dark-theme dashboard tracking €204M in revenue across product categories and sales channels. Forecast vs actuals, category breakdowns, and marketing attribution — built for executive review.

  • Power BI
  • Dark Theme
  • Area Chart
  • Time Intelligence
app.powerbi.com / kqn-regional-sales
KQN Regional Sales Dashboard

KQN — Regional Sales Dashboard

International sales performance across 8 countries — revenue vs target, category breakdown, and regional trends. Built for a team that needs to track progress across borders at a glance.

  • Power BI
  • Country Flags
  • Area Chart
  • Sales vs Target
app.powerbi.com / hartwell-sales-tracking
Hartwell & Co. Sales Tracking Dashboard

Hartwell & Co. — Sales Tracking

Netherlands sales breakdown by province — Noord-Holland, Zuid-Holland, and beyond. Revenue by day of week, sales rep performance, and weekly trend analysis in one clean view.

  • Power BI
  • Netherlands Data
  • Bar Chart
  • Time Analysis
// what we do

The boring
technical work
that matters.

Reliable pipelines. Consistent models.
Data you can trust.

// 01
Core
Power BI Dashboards
+
Clean, focused dashboards built on semantic models. Row-level security, shared metrics, and refreshes that just work — every time.
// 02
Core
Data Engineering
+
Automated pipelines that ingest from all source systems — scheduled, monitored, failure-handled, and built to scale without increasing complexity.
// 03
Advanced
Semantic Modeling
+
Centralised metrics, business-friendly naming, and fast query performance. Reusable across every report in the business.
// 04
Advanced
Azure & Microsoft Fabric
+
End-to-end Lakehouse architecture using Data Factory, Synapse, and Microsoft Fabric. Medallion layers (Bronze / Silver / Gold) built to last.
// 05
Core
Data Quality & Preparation
+
Standardised formats, de-duplication, and quality checks. A clear separation of raw and curated data — and a single trusted source of truth.
// 06
Core
SAP Integration
+
SAP HANA and SAP EWM connectors bridging your operational data to your BI layer. Hands-on experience with SAP-to-Power BI migration.
// the pipeline

Chaos in. Clarity out.

XLS Sales_Q3_FINAL.xlsx
CSV export_2024_v2.csv
SAP SAP HANA / EWM
API REST endpoints
CRM CRM export
DB SQL database
→
// data pipeline running
Bronze ingest raw ✓
Silver clean & conform ✓
Gold build model ✓
Semantic define metrics ✓
→
app.powerbi.com / trusted-report
Revenue
€2.4M
↑ 12% vs prior
Margin
38.2%
↑ 2.1pp
Weekly revenue trend
→ Refreshed automatically at 06:00. Same numbers everywhere. Trusted by everyone.
✓ accurate ✓ on time ✓ trusted
// the chaos
Spreadsheets, exports, live systems. All formats. All inconsistencies.
// the machine
Automated pipelines clean, conform and model your data into a single trusted foundation.
// the result
One dashboard. Accurate numbers. Refreshes itself. Everyone trusts it.
// how we build it

From raw data to
trusted decisions.

Click each layer to see what happens inside it.

// sources
SAP HANA / EWM
SQL Databases
APIs & Flat Files
ERP / CRM
// 01
Bronze
Raw Ingestion
+
Data lands exactly as it arrives — untransformed, append-only. Schema validation runs here: correct columns, correct types. If something is structurally wrong, it is caught before it goes anywhere. Business-level dirty data — duplicates, nulls, wrong entries — is expected and passes through. That is Silver's job.
Azure Data Factory Fabric Pipelines Data Lake Schema Validation
// 02
Silver
Clean & Conform
+
Business rules applied, errors fixed, duplicates removed. Lookups enriched — product categories, valid country lists, reference IDs. SCD logic applied where history needs tracking. Date formats, currency fields and column naming aligned across every source system so datasets can be joined without surprises.
PySpark Fabric Notebooks T-SQL SCD Logic
// 03
Gold
Business Model
+
Kimball-style star schema. Fact tables, dimension tables, defined relationships. KPIs and aggregations pre-calculated once — revenue totals, margin, units sold — agreed on and stored here, not recalculated independently in every report.
Star Schema Kimball Synapse Aggregations
// 04
Semantic
Shared Model
+
Business-friendly naming, DAX measures, row-level security. Every report reads from the same model — so Revenue means the same thing in every dashboard, every time.
Power BI Dataset DAX Measures Row-Level Security
// 05
Output
Trusted Insights
+
Dashboards and reports built on solid foundations — they refresh on time, show accurate numbers, and actually get used. The boring part is done. Now the interesting part begins.
Power BI Reports Scheduled Refresh Executive Dashboards
// built on Microsoft Fabric Azure Synapse SAP HANA Databricks PySpark T-SQL
// client feedback

What our clients say.

"

They brought real structure to how we track and report on our projects. We now have clear visibility across jobs that we never had before.

Director Oakwood Fort

What will your
data reveal?

Free discovery session — no sales pitch, just a clear-headed look at what your data could do.

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// based in the Netherlands, working with clients globally