Services / Data Analytics & BI
Analytics Audit
A complete analytics audit of your reporting, from the numbers on the dashboard all the way back to the data model feeding them. I review what you have, find what is wrong, slow, or untrustworthy, and hand you a clear, prioritized plan of exactly what to fix and in what order, before you spend another penny building on a shaky foundation.
Most reporting problems are invisible until they cost you. A report that quietly double-counts revenue, a model that takes ten seconds to load, a dashboard nobody trusts because the numbers never quite reconcile, these do real damage long before anyone names them. An analytics audit makes them visible. It is a complete, honest review of your reporting and the data beneath it, so you know exactly what is wrong and what fixing it is worth, rather than guessing.
I am a Microsoft Certified Power BI Data Analyst (PL-300) and Fabric Analytics Engineer (DP-600), and I have improved query performance by 40% on production reporting and rebuilt data models whose numbers nobody trusted. An analytics audit brings that diagnostic eye to your estate. Here is how it works.
What a complete analytics audit covers
An analytics audit is a structured review of your reporting from the front-end dashboards back to the data that feeds them, checking correctness, performance, design, and governance at every layer. It is deliberately end-to-end, because a problem on the dashboard usually traces to something deeper: a flawed measure, a bloated model, a broken refresh, or data that was never clean. A review that only looks at the visuals misses where the real issues live.
Concretely, the audit examines whether the numbers are correct and reconcile to source; whether the data model is sound or carries the quiet flaws that make reports slow and fragile; whether the DAX or calculations are efficient and right; whether reports load fast enough that people actually use them; whether access, refresh, and security are set up properly; and whether the design serves the decisions it is meant to. Each finding is documented with its severity and its fix, so nothing is hand-waved.
WHAT YOU GET
Know exactly
what to fix.
An end-to-end review with an honest, prioritized plan of what to fix and in what order.
- Correctness checked to sourceWhether your numbers actually reconcile, so you find the quiet errors, double-counts, and wrong measures before they drive a bad decision.
- Model and DAX reviewedThe data model and calculations assessed for the flaws that make reports slow, fragile, or subtly wrong, with each issue and its fix named.
- Performance diagnosedWhere and why reports are slow, measured rather than guessed, so the fixes target the real bottlenecks instead of folklore.
- Governance and data quality assessedRefresh, access, security, and the state of the underlying data, so you know whether the foundation is sound or quietly at risk.
- A prioritized planEvery finding ranked by severity and effort, so you get an honest roadmap of what to fix first, not a vague list of complaints.
How the audit works
The audit is methodical and evidence-based, because the whole value is in findings you can trust and act on.
Understand the estate. I start with what you have and what it is meant to do, the reports, the sources, the users, so the review is grounded in how the reporting is actually used rather than a generic checklist.
Check correctness first. I test whether the numbers reconcile to source, because a report that is fast and beautiful but wrong is the most dangerous kind, and correctness is the foundation everything else sits on.
Review the model, DAX, and performance. I examine the data model and calculations for flaws and measure where time is actually spent, so performance and reliability issues are diagnosed, not assumed.
Assess governance and data quality. I check refresh, access, security, and the state of the underlying data, so risks that do not show on the dashboard are surfaced before they bite.
Deliver a prioritized plan. I hand over documented findings, each with severity, impact, and the fix, ranked so you know exactly what to tackle first and what it is worth.
Why an audit before you build
The most expensive mistakes in analytics are made before anyone realizes the foundation is flawed. Teams keep building reports on a broken model, keep trusting numbers that do not reconcile, and keep adding to a slow, fragile estate, because no one ever stopped to assess it honestly. An audit is the cheap step that prevents the expensive ones, by telling you the truth about what you have before you invest more in it.
It is also the step that protects trust. Once people catch a report being wrong, they discount all of your reporting, and that lost confidence is hard to win back. An audit finds those errors on your terms, quietly and early, so they are fixed before they surface in a board meeting. Whether the outcome is a short list of quick wins or a clear case for a rebuild, you come away knowing exactly where you stand, which is worth far more than continuing to guess.
Who an analytics audit is for
It suits any team that suspects something is wrong but cannot pin it down: reports that disagree, numbers nobody fully trusts, dashboards too slow to use, or a reporting estate that has grown messy over the years. It is also the right first step before a significant investment, a migration, a rebuild, a new platform, because knowing the true state of what you have shapes every decision that follows.
And it is valuable precisely because it is independent. An honest outside review, from someone who builds these systems and knows where the bodies are buried, surfaces things an internal team is too close to see or too invested to raise. The point is not to criticize; it is to give you a clear, trustworthy picture so your next move is the right one. If the audit leads to fixing specific issues, that work, from performance tuning to model rebuilding, follows naturally from the plan.
Timeline and cost
An audit of a focused reporting estate can often be completed in a few days to a week, ending in a clear, prioritized findings document. A larger or messier estate takes longer, because a thorough review that actually traces problems to their root is worth far more than a quick skim that only lists symptoms.
Judge the cost against what flawed reporting costs you: decisions on wrong numbers, time lost to slow reports, and money sunk into building on a weak foundation. An audit is a modest investment that routinely saves many times its cost by catching those before they compound. For Microsoft's own optimization guidance, see Microsoft Learn. A complete analytics audit replaces guesswork with a clear, honest picture of exactly where your reporting stands and what to do next.
Frequently asked questions
What is an analytics audit?
An analytics audit is a complete, structured review of your reporting from the front-end dashboards back to the data feeding them. It checks correctness, performance, data model quality, and governance, then delivers a prioritized plan of exactly what to fix and in what order, so you know the true state of your reporting.
What does the audit actually review?
Whether your numbers reconcile to source, whether the data model and DAX are sound or carry quiet flaws, where and why reports are slow, whether refresh, access, and security are set up properly, the state of the underlying data, and whether the design serves real decisions. Each finding is documented with its severity and fix.
Why not just fix the problems directly?
Because you cannot fix well what you have not properly diagnosed. Jumping to fixes often treats symptoms while the real cause, a flawed model or dirty data, stays in place. The audit finds the root issues and ranks them, so the fixes that follow target what actually matters rather than the most visible complaint.
Will you fix the issues the audit finds?
Yes, if you want. The audit stands on its own as an honest assessment and plan, and the remediation, performance tuning, model rebuilding, data cleaning, follows naturally from it. Some teams take the plan and act internally; others have me carry out the fixes. Either way, the audit gives you the roadmap.
Is an audit worth it before a migration or rebuild?
Very much so. Knowing the true state of what you have, what is sound, what is broken, what is worth keeping, shapes every decision in a migration or rebuild. Auditing first prevents carrying old flaws into a new platform and makes sure the investment goes where it actually pays off.
What do I receive at the end?
A clear, documented set of findings, each with its severity, business impact, and the recommended fix, ranked into a prioritized plan. You come away knowing exactly where your reporting stands, what to fix first, and what each fix is worth, rather than a vague sense that something is off.
Not sure if your reporting holds up?
Tell me what you have, and I will review it end to end and hand you an honest, prioritized plan of what to fix.