110 Analytics, a data analytics consultancy in Malta, builds and runs Power BI reporting for established companies, typically turning over roughly €1M to €10M a year. The reports sit on a data warehouse in the client's own account. Every number has one agreed definition, so every report reads the same figure. We do not sell Power BI licences and we do not run training courses.
You will recognise this if you already use Power BI
If you run a company in Malta and Power BI is already installed somewhere, one of these will probably sound familiar.
- We have Power BI, but the board pack is still built in Excel.
- Finance and sales bring different revenue figures to the same meeting.
- Only one person knows how the reports are built, and they are on leave.
- The refresh failed again and nobody noticed until Monday.
- We have dozens of reports and nobody knows which ones are still used.
- Every new question means a new report, and another wait.
- We bought the licences. Nobody opens the dashboards.
- Someone still exports from the accounting system every month and pastes it in.
Why Power BI reports stop being trusted
Power BI reports lose trust when each one connects to a different system and defines the numbers its own way. One report reads revenue from the accounting system, another from the CRM, a third from a spreadsheet somebody updates by hand. All three are called revenue, and none of them match.
The logic that turns raw rows into a figure lives inside each report, written by whoever built it. When that person moves on, nobody can say why margin is calculated the way it is.
When a column is renamed in the finance system, the refresh can fail. Somebody then rebuilds the figures in Excel the night before the board meets.
The dashboard is still there, but nobody believes it. A report nobody believes is worse than no report. It looks like progress while the real numbers drift back into spreadsheets.
What actually fixes it: the layer under Power BI
The fix we build is not a better Power BI report. It is one warehouse that every system loads into, with one written definition for every number, sitting between your systems and your reports.
A data warehouse is a single place where copies of your business data are collected, cleaned and kept in a shape built for asking questions. Every system you run loads into it overnight, on a schedule, without anyone exporting a file. Power BI then reads from one place instead of several.
We agree with your team what counts as revenue, an active customer or a late order, and we write it into the model. Every Power BI report inherits that definition. When the board pack and the sales dashboard both say revenue, they compute it the same way from the same rows.
The warehouse lives in your own environment, and you own it start to finish. If we parted company tomorrow, it would keep running and the reports would still be yours.
What we build in Power BI
The reports are the visible part. Most of the work sits underneath them.
The warehouse underneath
Every system you run loads into one warehouse on a schedule, overnight. Power BI reads from there, not from each system separately.
One definition per number
Revenue, margin, an active customer: agreed once with your team, written into the model, inherited by every report.
A shared semantic model
One model that many reports read from, so a definition is changed once and the change shows up everywhere.
Reports by role
The whole business on one screen for leadership, and each department's numbers at the depth it works at. Access is set by role, so people see what their role needs.
Reports that send themselves
Scheduled refresh and delivery, so the pack lands in the right inboxes on the right morning without anyone building it.
Flags raised by rules
A KPI behind target or an order stuck too long in one stage is flagged by a rule, not by someone happening to notice.
Who sees what
Three definitions of revenue become one
How to choose between Power BI and Looker Studio
If your company runs on Microsoft 365 and your finance team works in Excel all day, Power BI is usually the right choice. The reports sit in the same world as the files people already open.
If your company runs on Google Workspace and much of your revenue starts in Google Ads, Looker Studio is usually the better fit. BigQuery is then the warehouse underneath. We build that too, and cover it on our Looker Studio and BigQuery page.
Either way, the tool is the smaller decision. The definitions live in the warehouse, not in the reports, so a change of tool means rebuilding the screens, not the numbers. We recommend one before the build, based on what you already run, and we have no licence to sell you either way.
Already have Power BI reports? Here is what changes
If you already have Power BI reports, we do not start again for the sake of it. We start with the semantic models behind them.
Where reports have grown one at a time, each may carry its own model, connected to a different system, with its own version of every measure. During the audit we list them: what each model connects to, which measures it defines, who opens the report and who keeps it running.
In the build, those models give way to one shared semantic model on the warehouse. Revenue, margin and an active customer are defined once, as measures in that model, and the reports worth keeping are reconnected to it. Reports that repeat each other are folded together, and we suggest retiring the ones nobody opens.
Scheduled refresh moves to after the overnight load, so the model refreshes from finished tables rather than from live systems. Access moves into the model too. Rules by role decide which rows each person sees, so finance, operations and sales can open the same report and each see their own part.
Your Excel users keep Excel. They can connect to the same semantic model and build pivot tables on the agreed measures. The spreadsheet on the finance lead's screen and the dashboard in the board meeting then read the same figure.
The person who has been building and fixing the reports keeps building, on a model that reads from the warehouse rather than from each system. Less of their time goes on exports and repairs.
Power BI or Looker Studio: which should you use?
Both are capable reporting tools. The deciding factor is usually where your company already works, because that is where your people will open the reports.
| Power BI | Looker Studio | |
|---|---|---|
| Your office runs on | Microsoft 365 and Excel | Google Workspace |
| Your marketing runs on | Any mix of platforms | Google Ads and Google Analytics |
| People open reports from | Inside Microsoft 365 | Inside Google Workspace |
| Tool cost | Licences from Microsoft or your Microsoft partner | Standard version free from Google |
| Warehouse underneath | Built in your own cloud account | BigQuery, in your own Google Cloud account |
| Definitions live in | The warehouse, not the report | The warehouse, not the report |
What changes, in one business
A distribution business in Malta runs on Microsoft 365. Its accounting system, its ERP and its CRM each hold part of the picture. The finance team adopted Power BI some time ago and now has a folder of reports, each connected to a different system.
- Three systems, each feeding its own Power BI reports.
- Sales and finance bring different revenue figures to the weekly meeting.
- The board pack is still assembled in Excel by the finance lead, from exports.
- Only one person understands how margin is calculated in the reports.
- A question about which customers stopped ordering needs a new report and a long wait.
- All three systems load into one warehouse overnight.
- Revenue, margin and an active customer each have one written definition, agreed by sales and finance in the same room.
- Leadership opens one Power BI dashboard, current to yesterday. Each department sees its own numbers.
- The board pack builds itself from the same figures, and the finance lead reads it instead of making it.
- The question about lapsed customers is answered from one place, without a new report.
Nothing in the business was replaced. The accounting system, the ERP and the CRM carry on as before. What changed is what sits between them and the reports.
Your Power BI setup at the end of the first month
Implementation is the first month. Three to four weeks after you accept the quote, this is in place.
A live Power BI dashboard
The first dashboard, built around the decisions your leadership team actually makes, current to yesterday every morning.
Its sources, loading overnight
The systems behind that dashboard loading into your warehouse on a schedule, without anyone exporting a file.
Definitions, written down
Every number on the dashboard with one agreed definition, visible to anyone who asks where it comes from.
Access by role
Leadership, finance, operations and sales each set up to see what they need and not what they do not.
Everything in your name
The warehouse, the model and the reports in your environment, under your account.
A list of what comes next
The next reports and sources worth adding, in the order they matter, for the fractional team to work through.
How it works
- A data strategy callThirty minutes with Glen, free. Bring a rough picture of your Power BI reports: how many there are, what they connect to and who keeps them running. You get a straight answer on whether we are the right fit.
- The data auditAbout three hours with your team. Glen traces the figures in your Power BI reports back to the systems they come from, and looks at the models and measures behind them. He scores six dimensions with you, five levels each, and the audit ends with a quote.
- The buildThe warehouse comes first. Then one shared semantic model with the agreed measures, scheduled refresh and access by role, and the first dashboard on top. Your people agree the measures with us and tell us which reports they actually use. Three to four weeks from an accepted quote to a live dashboard.
- The fractional teamAn ongoing senior team keeps the model and its refresh healthy. It adds new sources and measures to the same model, and builds the next report on it.
What we do not do
- We do not sell Power BI licences. Those come from Microsoft or your Microsoft partner.
- We do not run Power BI training courses. If your team wants a formal course, a training provider is the right call.
- We are not IT. We do not replace your accounting system, ERP or CRM. We make the data inside them usable.
- We never take custody of the data. It stays in your environment.
- We do not lock you in. If we parted company, the warehouse and the reports would keep running.
Glen Sultana founded 110 Analytics after a career built where the numbers move daily. Our people have run analytics for tier-one companies, S&P 500 firms and high-growth technology businesses. Glen is the person on the first call, and he runs every data audit himself.
- Built in your environment, under your account
- No lock-in: if we part company, it keeps running and stays yours
- Based in Malta
Straight answers
Do you sell Power BI licences?
No. Licences are bought from Microsoft or your Microsoft partner. We build and run the reporting, and we can tell you who in your team will need access to it.
Do you offer Power BI training?
Not as a course. When a report goes live, we walk the people who use it through what it shows. Your Excel users see how to connect to the shared model. If your team wants formal Power BI training, a training provider is the right call.
Why not connect Power BI straight to our systems?
You can, and for a single report it can work. Once several reports each connect to several systems, each one tends to define the numbers its own way. A warehouse underneath gives every report the same definitions.
We already have Power BI reports. Do we start again?
Not usually. We keep the reports worth keeping and reconnect them to one shared semantic model on the warehouse. Duplicates are merged, and unused reports are put forward for retirement. The audit tells you which is which.
Why not ask our Microsoft partner or ERP supplier to build it?
They are the right people for licences and for the systems they support, and they keep those roles. Our work is the layer between your systems and your reports. That means one warehouse in your account, with definitions agreed with your team, so every Power BI report reads the same figure.
What does Power BI reporting cost?
Two separate costs. Licences are bought from Microsoft or your Microsoft partner. Our work is quoted at the end of the data audit. It depends mainly on how many systems feed the reports and what the first dashboard has to show.
Who owns the reports and the data?
You do: the warehouse, the semantic model and the reports all sit under your own account.
How long until we see a working dashboard?
Once you have accepted the quote, three to four weeks to a live dashboard. Implementation is the first month. After that, the fractional team keeps the model, the refresh and the reports running.
Can you handle a larger Power BI setup?
Most work is delivered directly by our own team in Malta. Larger and more complex projects draw on the partner network we have aligned, and the audit is where we work out which applies to yours.
The terms, in plain English
- Data warehouse
- One place where copies of all your business data are loaded, cleaned and kept, built for asking questions rather than running operations. Ours are built in your account.
- Ontology
- Your business's own terms, from customer and revenue to product and employee, each with one agreed definition and mapped to where its data lives.
- Semantic model
- The layer inside Power BI that holds the tables, relationships and measures a report reads. Built well, many reports share one. Built badly, every report has its own.
- Measure
- A calculation Power BI runs on demand, such as gross margin or revenue this month. It should follow the agreed definition, not the preference of whoever wrote it.
- Scheduled refresh
- Power BI reloading its data on a timetable, so reports are current when people open them. Ours run after the warehouse has loaded overnight.
- Tiered access
- Each person sees the numbers their role needs. Leadership sees the whole business; each department sees its own.