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Power BI Development

The Power BI development company that fixes the model, not just the visuals

BinaryBrill is a Power BI development company building the semantic model, DAX measures, report design and workspace governance that decide whether a dashboard is fast, trusted and actually opened. In-house senior engineers handle the whole stack, because most Power BI performance and trust problems trace back to the model long before anyone blames a visual.

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A senior engineer replies within 24 hours — not a sales rep.

Why Power BI reports are slow, wrong or simply ignored

The refresh takes forty minutes and the dashboard still looks wrong

Every table imports as a flat, unrelated extract with no shared date table and no query folding, so Power Query does the heavy lifting inside the refresh window instead of pushing it back to the source. By the time the report opens, half the room has already exported to Excel because they've stopped trusting the numbers to be current.

The same measure is defined three different ways across three reports

Gross margin was written as a DAX measure in one report, a calculated column in another, and a Power Query step in a third — and none of them agree during an edge case like a returned order. Nobody centralised the logic because nobody owns the model, so every report author invents their own version of the numbers that matter most.

One report needs a copy per region because there's no row-level security

Instead of one report filtered by who's viewing it, there are eleven near-identical copies, one per regional manager, each maintained separately. A measure change means updating eleven reports, and inevitably one gets missed, so two managers are looking at different logic without knowing it.

Capacity is maxed out and nobody can say which report is the cause

Refreshes are scheduled on everything, including reports nobody has opened in months, and a shared capacity groans under the weight of it. Without incremental refresh or a view into which datasets are actually expensive, the response to hitting the ceiling is buying more capacity rather than fixing the model.

What real Power BI development looks like underneath the visuals

The report canvas is the last five percent of the work. We spend the effort on the semantic model underneath it, because that's what determines whether refreshes are fast, numbers are trusted, and one report can serve everyone who needs it.

A star-schema model with one set of measures

Fact and dimension tables built to a proper star schema, with a dedicated date table and DAX measures defined once, centrally, rather than reinvented per report. Every report author references the same measure, so gross margin means the same thing everywhere it appears.

Row-level security instead of a report per audience

One report, filtered dynamically by who's viewing it, replaces the practice of building a near-identical copy per manager or region. A measure change happens once and every audience sees it immediately, with no risk of one copy quietly falling out of sync.

Incremental refresh and query folding, tuned deliberately

Refresh logic is designed to push transformation work back to the source wherever the connector allows, and incremental refresh policies mean only new or changed partitions reload. Refresh windows and capacity consumption become predictable instead of a growing risk.

Deployment pipelines with real workspace governance

Development, test and production workspaces with a defined promotion path, sensitivity labelling applied consistently, and a clear owner for every published report. Nothing reaches production without passing through a stage where it can be checked.

What this covers

Pick the piece you need, or bring us the problem and we'll tell you which applies.

Power BI Semantic Modelling & DAX Development

The foundation everything else sits on: a star-schema model with a proper date table and DAX measures defined once, centrally, so every report author works from the same source of truth instead of inventing their own version of a metric.

Star-schema semantic models with a proper date table and centrally defined DAX measures
Measure dictionaries documented so new report authors don't reinvent existing logic
Model performance tuned before report visuals are built on top of it

Power BI Dashboard & Report Development Services

Report design built for the audience and the decision it supports — fewer visuals, exceptions surfaced rather than buried, and a layout that answers the question someone actually opens the report to ask.

Reports scoped to a named audience and the decision they support, not a wish list of visuals
Interactive dashboards and drill-throughs built on the governed semantic model
Mobile-optimised layouts where the audience checks reporting away from a desk

Row-Level Security & Access Governance

Dynamic security that filters one report by who's viewing it, so a single build serves every region or manager instead of a maintained copy per audience — tested by signing in as real roles, not just configured and assumed to work.

Row-level security so one report serves every region without building a copy per manager
Security roles tested against real user accounts before go-live
Sensitivity labelling applied consistently across workspaces

Power BI Refresh & Performance Tuning

For dashboards already live and slow, we profile the model and refresh pipeline to find where time is being lost, then fix it — usually the model, not the visuals, and usually before anyone needs to touch the report design at all.

Incremental refresh and query folding tuned to keep refresh windows and capacity use predictable
Performance analyser reviews that isolate slow visuals from slow underlying model logic
Capacity usage reviewed so scheduled refreshes don't crowd out interactive use

Power BI Deployment Pipelines & Workspace Governance

The operational layer around Power BI that keeps a growing tenant navigable — workspace structure, promotion between environments, and a clear answer to who publishes what and where.

Deployment pipelines across development, test and production workspaces with sensitivity labelling
Workspace and naming conventions that prevent duplicate or near-identical reports accumulating
Governance documentation covering ownership, publishing rights and retirement of unused reports

The stack we build on

Chosen to fit the problem — not because it's what we used last time.

Power BI platform

Power BI Desktop
Power BI Service
Power BI Premium
Power BI Report Server
Power BI deployment pipelines

Modelling & query

DAX
Power Query (M)
Tabular Editor
DAX Studio
T-SQL

Data sources

Snowflake
SQL Server
Azure Synapse Analytics
Microsoft Fabric
PostgreSQL
SharePoint

Governance & delivery

Microsoft Entra ID
Row-level security
Azure DevOps
Git
Microsoft Purview

How we'll work together

Every stage ends with something in your hands — not a status update.

01
Model and report audit
We review the existing data sources, any current reports, and the questions each audience is actually trying to answer. For a new build, this step maps those same questions against the sources available to answer them.
You get: A written audit of data sources and any existing reports, with a recommended semantic model scope and a list of measures to centralise.
02
Build the semantic model
The star-schema model, date table and core DAX measures are built first, before a single visual. We validate the model against real data and reconcile key figures with any existing reporting so disagreements surface here, not after go-live.
You get: A documented semantic model with a measure dictionary, validated against a reconciliation check on real data.
03
Report build, security and refresh
Reports are built on top of the shared model, with row-level security configured and tested by signing in as real roles, and incremental refresh tuned against your actual data volumes and Power BI capacity.
You get: Production-ready reports on the shared model, tested row-level security, and a configured refresh schedule within capacity limits.
04
Deploy, govern, hand over
Deployment pipelines move the work through development, test and production workspaces, with sensitivity labelling and access set up. We hand over with a working session so your team can extend the model and reports themselves.
You get: A governed workspace structure across environments, deployment pipeline configuration, and a handover session with your team.

Where we've applied this

Retail

Store and channel performance dashboards with row-level security by region, so one report replaces the practice of building a copy per area manager.

Finance

Management reporting with centrally defined DAX measures and a documented model, so a figure on a dashboard matches the same figure wherever else it appears.

Healthcare

Capacity and utilisation dashboards with row-level security restricting identifiable detail to the staff entitled to see it, on a single governed model.

Logistics

On-time performance and cost-per-consignment dashboards refreshed on an incremental schedule that keeps pace with high shipment volume without exhausting capacity.

Manufacturing

Line and shift-level output dashboards built for a supervisor to check in seconds, drawing from the same model used for monthly plant comparisons.

Professional services

Utilisation and project margin dashboards partners can slice by client or team themselves, without asking an analyst to rebuild the view each time.

Questions buyers ask us

Is Power BI development the right fit for us, or do we need something bigger?

Power BI is a strong fit if you're already in Microsoft 365 and need interactive, self-service dashboards people can explore themselves rather than a fixed printable output. If most of your reporting is instead exact, page-numbered documents that go to customers or regulators — invoices, statements, regulatory returns — that's paginated reporting territory, which we cover separately under SSRS reporting. Many organisations need both, built on the same underlying model.

Should we hire Power BI developers directly or bring in a development company?

A single dashboard or a targeted performance fix suits a fixed-scope engagement with a Power BI development company — faster to start, no hiring overhead. If Power BI is going to be your primary reporting platform long-term with a growing number of reports and requests, having developers who know your model well, whether hired directly or embedded from a team like ours, tends to pay off. We'll give you an honest view of which shape fits during scoping rather than push either by default.

What drives the cost of a Power BI project, and how long does it take?

The state of the data underneath drives cost more than the number of visuals — a clean, modelled source is fast to build on, while data spread across systems with no shared key means model and cleansing work before a single report exists. Audience breadth is the other factor: one team's dashboard is a short engagement, while rolling out row-level security and governance across several departments is a bigger programme. A single well-scoped dashboard on clean data typically takes a few weeks; a full semantic model with several dependent reports usually takes one to three months.

How do you keep our data secure inside Power BI?

Row-level security is configured and tested against real user roles before go-live, not just set up and assumed to work. Sensitivity labelling is applied consistently across workspaces, and gateway and service account configuration follows least-privilege principles for on-premise data sources. Everything is built inside your own Microsoft 365 tenant — we don't route your data through infrastructure outside what you already control.

When is Power BI the wrong tool for what we need?

If the output has to be pixel-exact and printable — an invoice run, a regulatory submission, a statement pack — Power BI dashboards are the wrong tool for that job; paginated reporting through SSRS or Power BI Report Server is built for it instead. If your data volume and reporting needs are genuinely tiny, the overhead of a governed semantic model may be more than the situation calls for, and a well-built spreadsheet might do for now. We'd rather say so than build more than you need.

Can you take over Power BI reports built by another team or agency?

Yes, and it's a common starting point. We review the existing model and DAX measures, document what we find, and give an honest assessment of what to keep versus rework. Sometimes remedial work on a fundamentally sound model is the right call; sometimes untangling accumulated calculated columns and duplicated logic costs more than starting the model fresh. We'll tell you which situation you're in before committing to either.

Do we need a data warehouse before we can start on Power BI?

Not always. If your reporting draws from one or two clean systems, a well-built semantic model directly over them gets you a long way for less cost. A warehouse becomes worth building when figures need joining across systems that disagree with each other, or when you need history the source systems don't retain. We'll tell you honestly which situation you're in rather than defaulting to the larger project.

Who writes the code, and where are they based?

Our own in-house engineers in Sahibzada Ajit Singh Nagar, Punjab — 45+ of them, with over a decade of combined delivery experience, delivering for clients in 15+ countries. Nothing is subcontracted. You meet the engineers who will be on your project before you sign, and the person demonstrating the work each sprint is the person who built it.

Tell us which dashboard nobody trusts or nobody opens

Send us a note on your current reporting and where it's falling short. A senior engineer replies within 24 hours with a straight read on whether the fix is the model, the refresh, or the report design.

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