Power BI performance optimization consulting for reports your team has stopped waiting for

What this engagement covers

Power BI performance work is the job of finding where a report spends its time and removing the causes, rather than buying capacity to outrun them. Power BI gives you the diagnostic tooling to do it properly: Performance Analyzer in Power BI Desktop (opens in new tab) breaks each visual’s load time into the DAX query, the visual rendering and everything else, and Microsoft’s Power BI optimization guide (opens in new tab) sets out where the common costs sit. The work here is applying both to your reports, in the order that matters for your users.

Deliverables are the baseline timings, a ranked diagnosis, the optimized semantic models and reports, reconciliation of every changed number against the original, and a written findings report with before-and-after timings for the pages in scope. Work is performed remotely by senior US-based engineers from our Orange County, CA base, serving every US state, at one fixed price agreed before work starts after your free consultation.

Where this sits next to our other Power BI work

This engagement starts from reports you already have. If the report does not exist yet, or the existing one is beyond saving, our Power BI dashboard development engagement builds it properly from the start: a clean star-schema model, measures written once, and pages designed around the questions people actually ask. We will tell you in the consultation if a rebuild would cost less than tuning what is there.

The other neighbor is control of the wider estate. When the slowness comes from dozens of near-duplicate semantic models all refreshing against the same source, the fix is partly a governance decision about which model is the trusted one, which is what our Power BI governance consulting engagement settles. And if you are comparing outside help for this kind of work, our guide on how to choose a Power BI consultant lists the questions that separate a real diagnosis from a quick rewrite. Once the reports are fast, keeping them that way is ongoing work rather than a project — refresh failures, broken visuals and small changes are what our Power BI support and maintenance services cover, each scoped at a fixed fee.

Diagnosing a slow report: symptom, cause, fix

Most slow reports show one of six patterns. Each has a place it usually lives, a way to confirm it with evidence rather than intuition, and a fix that tends to hold. The table below is the diagnostic map we scope from; your findings report is the filled-in version for your own models.

The second row is where most engagements find their largest improvement. Microsoft’s star schema guidance for Power BI (opens in new tab) explains why: the engine is built to filter small dimension tables and aggregate one narrow fact table, and a model shaped that way makes most DAX simpler as well as faster.

Why we fix the model before the measures

DAX is where slowness becomes visible, so it is where most tuning effort goes first. But a measure is only as fast as the model it runs against. A well-written measure over a single wide table of every column from the source system will still scan far more than it needs to, and a clever rewrite on that model usually buys a short-lived improvement that disappears as the data grows.

So the diagnosis always looks at model shape and size before measure logic. Where the model is sound, measure rewrites are targeted and quick. Where it is not, reshaping it tends to speed up every report built on it at once, including ones nobody listed as slow. Either way, every changed measure is checked against the original output so that a faster report never means a different number.

Refresh performance is its own problem

A report can open quickly and still be a daily problem if its refresh runs for hours, fails overnight, or leaves the data stale by the time people look. The usual cause is not the source but the steps in between: a transformation that stops query folding, so Power Query pulls every row back and filters locally; or a full reload of years of history that has not changed since last night.

Restoring folding and moving large fact tables onto incremental refresh (opens in new tab), where the source supports it, typically shortens refreshes and makes them far less likely to fail. We confirm the source can support it before recommending it, and we document the partitioning policy so it is not silently undone the next time someone edits the query.

Who this fits, and who it does not

The usual fit is a team whose Power BI reports were built over time by capable people without much time to spare, and have grown slower as the data grew. The trigger is often a specific complaint: a leadership report that takes long enough to open that people ask for a spreadsheet instead, a refresh that fails a few mornings a month, or a capacity bill someone was told would fix it and did not.

It is a poor fit in two cases, and we will say so during the consultation. If the report was never modeled properly and the questions it answers have changed, rebuilding is usually the better purchase. And if the slowness sits in a source database or a network link outside Power BI, we will identify that and hand you the evidence, but tuning that system is a separate piece of work.

Delivery in three phases

The table shows scope and typical timeline rather than prices, because an honest number requires seeing how many reports and semantic models are involved, their data volumes, and how much of the model needs reshaping. For how our fee is set and what is fixed before anything starts, our fixed-fee process spells it out.

Everything produced is yours from the first day: the optimized models, the reports and the findings live in your own Microsoft tenant, never in ours. Nothing is published over your existing reports until you have reviewed the reconciled numbers, and the original versions are kept so any change can be rolled back.