Service 04 of 07
Data Engineering & Analytics
Dashboards that answer the questions leadership actually asks, built on data people trust.
What usually goes wrong
Most businesses do not lack data. They lack agreement on what it means.
- 01The same figure is worked out differently in different systems
- 02Analysts spend their time preparing data instead of using it
- 03Reports are assembled by hand, so they arrive too late to act on
How we do it
Process first, platform second
We pull the data out of your systems and model it against definitions everyone has agreed.
Then it goes in front of people through Power BI. Every number has one written definition and someone who owns it.
- Platforms
- Microsoft Azure
- SQL Server & Azure SQL
- Power BI
- Excel & Power Query
- Dataverse
- Engineering
- Data ingestion & integration
- ETL / ELT pipelines
- Dimensional data modelling
- Data quality & validation
- Warehouse & semantic layer design
- Analytics
- Executive dashboards
- Operational reporting
- Financial & sales analytics
- Self-service datasets
- Row-level security & governance
What changes
What you get out of it
- Agreeddefinitions
One written calculation per number, across every report.
- Automaticrefresh
Reporting that maintains itself instead of eating analyst time.
- Built fordecisions
Dashboards shaped around the questions leadership actually asks.
Anonymised, illustrative engagement profiles. They show the shape of the work, not audited client results.
- 01 · Manufacturing & Distribution
Four entities, one close process
Four trading entities on separate systems, one finance team. Month-end took nearly three weeks. Most of that was matching stock and intercompany balances by hand.
- 04 · Financial Services
Invoice handling without the re-typing
Supplier invoices arrived as PDFs across several mailboxes. A small team opened each one, read it, and typed it into the finance system.
FAQ
Questions we are asked most
Not always. Across two or three systems at moderate volume, a good Power BI model can be enough. A warehouse earns its place once you need history or heavier transformation.
Yes. We regularly pull from Salesforce, HubSpot, GoHighLevel, third-party APIs and operational databases alongside Microsoft platforms.
Either of us. We document the model and train your analysts, or run it for you under support.
Start here
Ready to talk about data engineering & analytics?
Tell us where the manual work sits, where the numbers disagree, or where your systems stop talking to each other. You will get a written point of view within one business day.