The Hidden Complexity Behind a Simple Power BI Report📊🧰
I have learned over the years of building many different Power BI reports for many different clients, that the reports that look the simplest are usually the ones that took me the most work to build. It is so important that the foundations are solid before building any Power BI report.
With all the attention AI is receiving at the moment, I think there is an even bigger conversation we need to have now about the work that goes on behind the scenes. Whether we are building a Power BI report or asking AI to analyse our information, there is one thing that hasn't changed. We need to be able to trust the data we're working with!
Welcome to the Iamdata Solutions Asset Management Newsletter – November 2026
When I hand over a really clean report, it can look almost too easy. A handful of KPIs, a couple of well chosen visuals, a layout that just makes sense the moment you open it. Sit that next to a report packed with charts, slicers, colours and clever interactions and the simple one can honestly look like I barely did anything.
But that simplicity is never an accident. It is the whole point, and it is where most of the effort actually went.
What People Actually Ask Me For
When I sit down with a manager or an operations team, nobody asks me for more visuals. What they ask is much simpler than that. Quite often it is as simple as these three questions. They want to know:
Are we improving?
Where are the risks?
What is driving our cost, our service levels, our performance?
A good report should walk them straight to those answers without making them go hunting. A lot of my design work is actually about taking things away. Stripping out the noise so the information that matters has room to breathe and can be seen.
The Part Nobody Sees - The SQL, ETL and the Data Model
Here is where most of the heavy lifting happens, and it is the part that never shows up in the finished report.
In most organisations, and most councils, the data never sits in one tidy place. It is scattered across the asset management system, GIS, finance, the CRM, a few spreadsheets, and whatever operational database has quietly grown up over the years. Pulling all of that together into something you can actually trust is where the real effort goes.
That is the quiet work that SQL, ETL and a solid data model are doing in the background for you:
The SQL cleans and shapes the data so it is consistent and genuinely usable.
The ETL automates the extract, transform and validate steps, which cuts out a lot of manual handling and the little errors that always sneak in with it.
The data model makes sure the relationships between assets, inspections, costs, locations and activities all line up before anything ever gets visualised.
When I get that groundwork right, the visuals can be built quite easily and the users are able to open the Power BI report and know they can just trust it. They are not wondering whether the numbers have been stitched together from three mismatched sources. They can believe what they are looking at, and that is really the whole point of the Power BI report.
Why a Calm Power BI Executive Page Beats a Busy One
One of the easiest traps to fall into is thinking that more visuals means more value. In my experience it almost never does. A busy page tends to overwhelm people and end up burying the very insight you were trying to highlight.
An executive page works best when it says the right thing quickly. A few strong KPIs, a trend or two, the exceptions, and a clear risk indicator will support far better decisions than a wall of charts all elbowing each other for attention.
A simple looking Power BI report does not mean less sophisticated. Usually, it is the opposite. A clean page reflects a deeper understanding of the business and much clearer thinking about what actually matters.
Every Power BI Visual Should Earn Its Place
My rough rule is this. If a chart, card, map or table does not help someone make a decision or answer a real question, it is probably just noise.
In asset management, the visuals that tend to earn their spot look like:
lifecycle forecasting visuals for renewal planning
map based views for spatial assets
trend charts for inspections or service requests
summary cards for the operational KPIs
Choosing the right visual is less about what looks impressive in a demo and more about what actually helps people act with confidence.
Turning Messy Asset Data Into Something Useful
Infrastructure data is genuinely technical, and there is so much of it! Think about every asset class a council looks after, and then add maintenance records, valuations, defects and condition data. Often the data are all sitting in different systems and different formats.
Getting that into meaningful reporting usually means data cleansing, spatial alignment, mapping out the business rules, and linking operational records back to asset hierarchies and financial information. It is fiddly, detailed work.
But the goal is never to show people the complexity. Asset managers do not want to stare at a raw mess of data. What they need is to understand condition, risk, cost, renewal needs, service impact and performance in a way that helps them plan for the long term.
AI Doesn't Make Bad Data Better
With all the excitement around AI at the moment, I think there is another really important reason we need to get our underlying data right.
Everything I've been talking about in this post, the data cleansing, validation, business rules, relationships and all that work nobody ever sees, is just as important for AI. In some ways, I would argue that it is even more important.
When I build a Power BI report, I spend a lot of time checking that the numbers make sense. If something doesn't look right, I can investigate the SQL queries, trace the records back to their source, check the relationships and work out where things have gone wrong.
But what happens when someone asks an AI tool a question about that same data? Imagine an asset manager asking AI, ‘Which of our roads are most at risk of failure over the next five years, and how much should we budget for renewals?’
If the underlying asset register contains incorrect construction dates, outdated condition assessments, missing assets or inconsistent replacement costs, the AI might produce an answer that looks perfectly reasonable, but as we all know AI tends to make things up when it hasn’t got all the information it needs and it could even present a convincing explanation of which roads need attention and why. AI can make incorrect information sound remarkably convincing and that is what's concerning me most.
With a traditional report, we might notice an unusual number, a missing value or something that just doesn't look right. AI can sometimes smooth over those inconsistencies and present its findings in such a confident, polished way that nobody thinks to question them. Of course, not every AI system behaves this way, and some are designed to identify missing information, provide source references and flag uncertainty. But those safeguards don't automatically make the underlying data correct. That is a real concern when organisations are increasingly looking to AI to help analyse information and support decisions.
I'm certainly not against AI. Quite the opposite. I think it has enormous potential to help councils make better use of the information they've been collecting for years. But we can't expect AI to magically fix years of inconsistent data collection, missing records or poorly defined business rules.
AI can help us find data quality problems, identify anomalies and even assist with cleansing. But we still need to establish what the correct information should be and validate the results.
And that brings me back to the point of this blog post.
Whether we're building a Power BI report, developing an automated reporting process or introducing AI into our organisations, the quality of the answers will always depend, in part, on the quality of the information we're giving these systems to work with.
All that work behind the scenes isn't becoming less important because of AI. If anything, it's becoming more important than ever.
The Best Power BI Reports Feel Effortless
The best Power BI reports are often the ones that feel effortless to use. But that simplicity doesn't happen by accident. It's usually the result of a great deal of careful work happening quietly behind the scenes.
Good reporting has never been about doing less. It is about managing the complexity so that the people using the reports don't have to. They can simply trust the information in front of them and concentrate on the insights that matter.
For example, let’s look at something as simple as a button on a Power BI report. To the end user, it is just a button. They click it, something happens, and they get on with their day. But behind that one click, a Power Automate flow might spring into action, execute a stored procedure in a SQL database, update records, generate information, send an email notification or kick off an entire business process.
With AI becoming an increasingly important part of how organisations analyse information and make decisions, I believe all that behind-the-scenes work is becoming more important than ever.
We can build beautiful Power BI reports and dashboards, and introduce increasingly sophisticated AI tools, but none of that technology can make up for data we can't trust. In fact, AI introduces another challenge. It can present incorrect or incomplete information so convincingly that the underlying problems become even harder to recognise.
The technology might be getting smarter, but that does not automatically mean our data is getting better. We still need people who understand the data, question its accuracy, investigate inconsistencies and put the work into getting it right.
And perhaps that is the most important message of all. No matter how sophisticated our reporting and AI tools become, the quality of the decisions we make will always depend on the quality of the information behind them.
If any of this sounds familiar, or you are tackling similar challenges in your own organisation, I'm always happy to have a chat, share experiences and compare notes. I'd love to hear from you.
I have worked on many different projects with my Local Government clients, from designing and developing Power BI Reports, to building SQL Server databases for spatial data, to managing and maintaining GIS and the Asset Management systems. If you'd like to discuss how we might work together, then please email Jill at ➡️ jill.singleton@iamdata.solutions
If you would like to receive the latest Newsletter Blog straight to your inbox, please subscribe here: ➡️ https://www.iamdata.solutions/subscribe
You can read all our Newsletters and Blogs here:➡️ https://www.iamdata.solutions/blog
You may also be interested in our Projects Page:➡️ https://www.iamdata.solutions/past-projects
Check out what our clients say about us here:➡️ https://www.iamdata.solutions/reviews
If you would like to see a particular topic covered in these newsletters, then please let me know about it. The chances are other people will be interested and would like to hear about it too! Please email me at: ➡️ jill.singleton@iamdata.solutions with your suggestions.
