Services

Reporting that holds, from the data up.

Three connected layers: the data foundation, the Power BI stack on top, and the automation around it. Taken on together, or wherever you need a gap closed.

01 Power BI, end to end Semantic models, DAX, deployment and governance
02 The SQL data layer T-SQL, query performance and warehouse integration
03 Power Platform automation Power Automate, SharePoint and Office Scripts

Power BI, end to end

Stack

Power BI DAX Power Query M Tabular modelling Power BI Service RLS

I build the full Power BI stack: semantic models, DAX measures and Power Query transformations, designed to stay correct as the data and the business change. The work runs from modelling through report and dashboard design to deployment on the Power BI Service and the governance around it: workspaces, semantic models, refresh and access. The aim is reporting that operational teams and leadership can rely on without second-guessing the numbers, and that doesn't quietly break the next time a source shifts.

What's included

Semantic (tabular) modelling and star-schema design
DAX measures, calculation groups and time intelligence
Power Query / M transformations and refresh strategy
Report and dashboard design for operational and executive audiences
Deployment, workspace structure and semantic model governance
Row-level security and access control

When this fits

You have data, but the reporting is fragile, inconsistent or simply not trusted. Or you're setting up Power BI properly for the first time and want it built to last.

The SQL data layer

Stack

T-SQL SQL Server Azure SQL Query optimisation Data warehousing Data modelling

Reporting is only as good as the data underneath it. I work at the data layer, writing and optimising T-SQL, shaping clean and queryable structures, and integrating sources into a warehouse pattern that Power BI can sit on cleanly. That covers query performance, sensible modelling at the database level, and reliable, repeatable loads. The point is to get the numbers right and fast before they ever reach a model, so the reporting layer stays simple.

What's included

T-SQL development: queries, views and stored procedures
Query performance tuning and indexing review
Data warehouse and reporting-layer modelling
Source integration and repeatable load patterns
Data quality and reconciliation checks
SQL Server and Azure SQL implementation

When this fits

Refreshes are slow, numbers don't reconcile across sources, or report logic has crept into places it shouldn't be. You need the foundation fixed for good.

Power Platform automation

Stack

Power Automate SharePoint Office Scripts Excel automation

A lot of operational reporting is held together by manual steps: spreadsheets emailed around, data re-keyed, approvals chased. I automate that connective tissue with Power Automate, SharePoint and Office Scripts, so data collection and routine workflows run reliably and leave a clean trail. The point is to remove the fragile manual stages that quietly corrupt operational data before it reaches a report.

What's included

Power Automate flows for data collection and routing
SharePoint list and library structure and integration
Office Scripts for Excel and spreadsheet automation
Approval and notification workflows
Replacing manual re-keying with reliable capture

When this fits

Your reporting depends on manual steps that are slow, error-prone, or understood by only one person. You want the routine work to run itself, dependably.

Get in touch

Not sure which layer you need?

Most engagements touch more than one. Tell me what the reporting has to do, and I'll tell you where the work actually is.

Discuss a project