Business intelligence, or BI, is the practice of turning the data held in a company's systems into figures people can decide by. It covers three jobs: bringing the data together in one place, agreeing what each number means, and showing it in dashboards and reports that update on their own. A BI tool such as Power BI or Looker Studio is only the visible part. 110 Analytics, a tech and AI company in Malta, builds all three in the client's own account.
You will recognise this
If any of these came up in your last management meeting, this page is written for you. None of them starts with the tool.
- We bought a BI tool. Nobody opens the dashboards.
- Every department brings its own number to the meeting, and the meeting is spent on which one is right.
- The board pack is still built in Excel, by hand, after the month has closed.
- Every new question goes to the same person, and waits behind the monthly pack.
- When our finance lead is on leave, the reporting stops.
- We have years of data and still make the big calls on gut feel.
- We want to try AI on our numbers, but we do not know which version it should read.
Why business intelligence stops being trusted
Business intelligence stops being trusted when the tool arrives before the numbers underneath it are sorted out. The tool is the visible part, so it tends to come first, and the first report feels like a step forward.
Then each report connects to a different system and defines the numbers its own way. Sales counts revenue when a deal is signed, finance when it is invoiced, and both are right by their own definition. Put both on one screen and they simply disagree faster.
Underneath, someone still exports, pastes and reconciles by hand, so the reporting is only as current as their last free afternoon. When the figures are challenged, leadership goes back to the spreadsheet it trusts, and the big decisions go back to instinct.
What does business intelligence include?
Business intelligence has three layers, and only the top one is visible. At the bottom is the data: every system you run, loaded on a schedule into one warehouse, with nobody exporting a file. In the middle are the definitions: what counts as revenue, margin or an active customer, agreed once with your team and written into the model. At the top is what people see: dashboards, reports that send themselves, and an AI layer that answers questions in plain language.
It is tempting to start at the top, with the tool. We start at the bottom, because a dashboard can only be as good as the numbers it reads. When the definitions live in the model, every report inherits them, so the meeting can move from which number is right to what to do about it.
That is what ‘stop guessing’ means in practice. Not more charts, but one version of every number, current to yesterday, that leadership can act on.
The tool is the smallest decision. We build in Power BI or Looker Studio, and recommend one before the build, based on what you already run and who will use it. We sell no licences, so we gain nothing from which one you pick.
What we build
The dashboards are the visible part. Most of the work sits underneath them, and all of it sits in your account.
One warehouse, in your account
Every system you run loads into it overnight, on a schedule. It is built in your environment, under your credentials, and it keeps running if we part company.
One definition per number
Revenue, margin, an active customer: agreed once with your team, written into the model and inherited by every report.
Dashboards 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.
Reports that send themselves
The monthly pack builds itself from the same figures and lands in the right inboxes on schedule, without anyone assembling it.
Flags raised by rules
A KPI behind target or a load that fails is flagged by a rule, not by someone happening to notice.
An AI layer on the same model
Ask a question in plain language, and the answer comes from your own warehouse and definitions, not from a guess. It is switched on last, once the definitions can support it.
What business intelligence changes, in one business
A wholesale and retail business in Malta runs an ERP for stock, a point of sale in its shops, an accounting system and a CRM for its trade customers. It switched on a BI tool some time ago, and now has a folder of reports, each connected to a different system.
- Shop and trade revenue, read straight from each system, never add up to what finance reports.
- The board pack is assembled in Excel by the finance lead, from exports, after the month has closed.
- Only one person understands how margin is calculated in the reports.
- A question about which trade customers are buying less needs a new report and a long wait.
- Buying decisions lean on what the buyer remembers selling last season.
- The ERP, the point of sale, the accounting system and the CRM load overnight into one warehouse in the business's own account.
- Revenue and margin each have one written definition, agreed by sales and finance in the same room.
- Leadership opens one dashboard, current to yesterday. The shops, the trade team and finance each see their own numbers.
- The board pack builds itself from the same figures, and the finance lead reads it instead of making it.
- Which trade customers are buying less is answered from one place, and a regular customer who stops ordering raises a flag by rule.
- Buying decisions start from what actually sold, by shop and by season.
Nothing in the business was replaced. The four systems carry on as before. What changed is the model between them and the reports, and the business owns it.
A BI tool on its own, or business intelligence on a model you own?
Both use the same kind of software. The difference is what sits underneath the reports, and who owns it.
| A BI tool on its own | BI on a model you own | |
|---|---|---|
| Reads from | Each system separately | One warehouse, loaded overnight |
| Definitions live in | Each report, written by its builder | The model, agreed once with your team |
| Two reports on revenue | Can disagree | Read the same figure |
| When the builder leaves | The logic leaves with them | The logic stays, written down |
| The monthly pack | Often rebuilt by hand | Builds itself on schedule |
| AI on your numbers | No agreed version to read | Answers from the same model |
| Who owns it | Whoever built each report | You, in your own account |
What you have at the end of the first month
Implementation is the first month. Three to four weeks from an accepted quote, a dashboard is live, and this is the foundation under it.
A warehouse in your account
The systems behind the first dashboard loading overnight, built in your environment, under your credentials.
Written definitions
Every number on the first dashboard defined once in plain English, agreed with your team and modelled in the warehouse.
A live dashboard
The first view in Power BI or Looker Studio, built around the decisions your leadership team makes, current to yesterday.
Access by role
Who sees what, set from the start, so each team sees its own numbers.
A list of what comes next
The next sources, reports and questions worth adding, in the order they matter, for the fractional team to work through.
How it works
- A strategy callThirty minutes with Glen, free, with no pitch deck. You leave knowing where your data is fragmented, the one view that would change how you run the business, and whether 110 Analytics is the right fit.
- The data auditAbout three hours with your team, mapping where each figure comes from and which steps are done by hand. The audit ends with a quote.
- The buildThree to four weeks from an accepted quote to a live dashboard. Implementation is the first month. Your team agrees the definitions with us; we do the building.
- The fractional teamAn ongoing senior team keeps the loads running and the definitions current, and keeps finding the next thing worth looking at.
What we do not do
- We do not sell BI tools or licences, so we gain nothing from which one you choose.
- We do not replace your accounting system, ERP or CRM.
- We do not take custody of your data. It stays in your own account.
- We do not lock you in. If we parted company, the warehouse and the reports would keep running, and stay yours.
- We do not automate decisions. The dashboard shows what moved; the decision stays with your leadership team.
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
Is business intelligence the same as Power BI?
No. Power BI is one BI tool, made by Microsoft, and Looker Studio, made by Google, is another. Business intelligence is the whole job: bringing the data together, agreeing what each number means and showing it to the people who decide. The tool is the visible part, and the smallest decision in the project.
Do we need a data warehouse for business intelligence?
In the way we build, yes. For a single report from a single system, a BI tool can connect straight to it. Once several reports read from several systems, each tends to define the numbers its own way. The warehouse gives every report one set of definitions and one place to read from, and we build it in your own account.
Which BI tool do you use?
Power BI or Looker Studio, chosen with you before the build. Power BI tends to suit companies on Microsoft 365 and Excel; Looker Studio tends to suit companies on Google Workspace and Google Ads. We sell no licences, so the recommendation follows what you already run.
How long until we see a first dashboard?
Three to four weeks from an accepted quote to a live dashboard; implementation is the first month. Before that comes a free thirty-minute strategy call with Glen, and a data audit of about three hours with your team.
Who owns it?
You do, outright. The warehouse, the definitions and the reports sit in your environment, under your account and your credentials. If we parted company, it would keep running and stay yours. There is no 110 platform underneath it and no licence to renew with us.
How much does business intelligence cost?
We quote the work at the end of the data audit, because the figure depends on how many systems you run and what the first dashboard needs to show. The strategy call is free. Any tool licences come from the vendor or its partner, and the cloud provider bills the warehouse's running costs to you directly.
Do we have to replace our systems?
No. Your accounting system, ERP, CRM and spreadsheets keep their jobs. We read their data on a schedule, read-only wherever the system allows, and bring it together for reporting.
Who provides business intelligence services in Malta?
110 Analytics is a tech and AI company in Malta that builds business intelligence for established companies. We load your systems into a warehouse in your own account, agree the definitions with your team and build the dashboards, scheduled reports and AI layer on top. An ongoing fractional team then keeps it running.
BI terms, in plain English
- Business intelligence (BI)
- Turning the data in your systems into agreed figures people decide by: the data, the definitions and the reports, together.
- BI tool
- The software that draws the dashboards and reports, such as Power BI or Looker Studio. The visible part of BI, not the whole of it.
- Data warehouse
- One store of copies of your business data, loaded on a schedule and organised for questions. Ours are built in your account.
- Ontology
- Your business's own terms, from customer and revenue to product, each defined once and mapped to where its data lives.
- Dashboard
- A screen showing the current state of the measures a role acts on, refreshed automatically.
- Tiered access
- Each role sees the numbers it needs, at the depth it works at. Leadership sees the whole business.