Guest Articles / Guest Opinion
Self-service Power BI: what IT teams need to get right
GUEST OPINION: Power BI is hard to avoid now. It holds close to a third of the business intelligence market, the category of software that turns raw company data into reports and dashboards, and it sits inside the Microsoft 365 estate most organisations already run. For business users, that accessibility is the whole appeal: a finance analyst or an operations manager can connect to a data source and build something useful without raising a ticket. For the IT team that ends up supporting all of it, the same accessibility is where the work starts.
Most IT departments recognise the sequence. A few keen users start building reports. The reports prove useful, so more people build more of them. Within a year there are dozens of dashboards across the business, several showing different numbers for what should be the same figure, and the questions begin landing with IT. Why does the sales report disagree with the finance one? Why did this dashboard break when the source file changed? Who actually owns it? Self-service analytics has arrived, and it has arrived without much of a plan.
None of that is a reason to avoid Power BI. The lesson is to handle the rollout deliberately rather than let it happen by accident, and most of what goes wrong comes down to a few decisions IT is well placed to make.
The tool is rarely the hard part
When a Power BI estate gets messy, the cause is almost never the software. It is the absence of a shared foundation underneath it, and three issues account for most of the trouble.
The first is duplicated data. When every report author connects to raw sources and shapes the data their own way, you end up with as many versions of “revenue” as there are reports. A governed, certified dataset that several reports build on fixes this, but someone has to design and publish it.
The second is weak data modelling. Business users arriving from Excel tend to pull everything into one wide table, which works until it does not, usually when a measure starts double-counting or a filter stops behaving. Power BI is built around a star schema, a structure that separates the things you measure from the things you measure them by. Reports built that way hold up as the data grows. Reports built on a flat table tend to fail in ways that are slow and frustrating to diagnose.
The third is refresh and ownership. A dashboard nobody maintains drifts out of date or breaks when a column is renamed upstream. Deciding who owns each report, and how its data refreshes, is dull work that prevents a great many support tickets later on.
Governance that helps rather than blocks
The instinct, when reporting sprawls, is to lock it down. That tends to push users back to emailing spreadsheets around, which is the situation you were trying to leave behind. The more workable approach is to give people a safe place to build: a shared, certified data layer they can trust, clear guidance on what “good” looks like, and a light approval step for anything that becomes a company-wide
That model lets the business keep the speed it values while IT keeps oversight of the data that matters. It treats report authors as partners rather than a problem to be contained, which is usually how you earn their cooperation instead of their workarounds.
The skills gap is the real lever
Here is the part that gets the least attention and matters the most. Most of the mess in a self-service Power BI estate traces back to a skills gap. People building reports without ever being taught to model data properly will reproduce the same avoidable problems, however good your policies are.
That makes training one of the highest-return things IT can sponsor. A business user who understands evaluation context in DAX, the formula language Power BI uses for calculations, and who reaches for a star schema by habit, builds reports that do not generate tickets. Self-teaching from scattered videos gets people started, but it tends to leave gaps in exactly those modelling habits. A focused course closes them faster. Red Eagle Tech, a Microsoft Solutions Partner, runs a structured Power BI masterclass built around producing real, well-modelled reports rather than working through theory, which is the difference that shows up later in your support queue.
Training your most active report authors first has a multiplier effect. They become the people everyone else asks, which raises the standard across the business without IT having to inspect every file.
Where Power BI fits, and where it does not
For most organisations already on Microsoft 365, Power BI is the practical default, largely on licensing and integration. Weighing the trade-offs against the other tools in the category still matters rather than assuming it wins every contest, particularly on cost, visualisation and how a team is set up. For an IT team standardising on one platform, the fact that Power BI already lives inside the estate you manage usually settles the matter.
The shift for IT
Supporting Power BI well starts with the foundation people build on. Design a shared dataset people can trust, set out what a good report looks like, and invest in the skills of the people doing the building. Do those three things and self-service analytics stops being aanswers, produced by the people closest to the question, on data the whole business can rely on
IT’s role changes along the way, from the team that builds every report to the team that makes good reporting possible. For most departments, that is a far better use of the time.
