Microsoft Power BI
The default BI tool of the Microsoft world, with Copilot for plain-language analysis.
- Ubiquitous, affordable entry, huge talent pool
- Lives beside Excel and Teams
- Full Spanish localisation
All guides Data
Ask your numbers a question. In plain words.
The numbers exist. They are in the ERP, the store, the spreadsheets. What is missing is the analyst to answer, today, why margin dipped in March. Ask-your-data AI answers business questions in plain language, from your real data. This guide covers how it works, the serious platforms, and when to buy versus build.
- Plain wordsquestions, not queries
- Your dataanswers with the numbers
- Self-serveno analyst bottleneck
- Alertschanges find you first
What an AI data analyst is
An AI data analyst connects to where your numbers live and answers questions asked in ordinary language: which products lost margin last quarter, which clients are slipping, how this month compares. It writes the queries, draws the chart, and increasingly watches your metrics and tells you when something moves.
01
It connects to your data
The accounting system, the store, the CRM, the spreadsheets. Read-only, where the numbers already are.
02
You ask like you would ask a person
Sales by product line versus last year. Which customers stopped ordering. No SQL, no report request ticket.
03
It answers with the working shown
The number, the chart, and what it measured, so a wrong assumption is visible instead of hidden.
04
It watches so you do not have to
Metrics that matter get monitored, and the anomaly finds you before the month-end surprise.
When this solution makes sense
A good fit if
- Decisions wait days because reports wait for the one person who can pull them
- Your numbers live in several systems and meetings argue about whose export is right
- Managers want answers mid-meeting, not a dashboard request ticket
- Excel is the de facto BI tool and it is creaking
- Surprises show up at month-end that the data knew about in week one
Probably not yet if
- The data is so scattered or dirty that definitions come first
- One person genuinely answers everything fast already
- You want predictions and forecasting before basic visibility exists
- Nobody will act on the answers anyway
What changes
Answers at the speed of the question
The margin question gets answered in the meeting where it came up, not in next week's deck.
One version of the truth
Everyone asks the same source, so meetings argue about decisions instead of whose number is right.
The analyst bottleneck dissolves
Routine questions stop queueing behind the one person who knows the database.
Problems surface early
Watched metrics raise their hand when they move, weeks before the month-end review would have noticed.
What teams use it for
- Sales and margin questions on demand
- Customer and product performance
- Cash and receivables visibility
- Inventory and purchasing signals
- KPI monitoring with alerts
- Board and investor reporting
The established platforms
These platforms lead the category.
ThoughtSpot
Search-first analytics where asking questions IS the product.
- The purest ask-your-data experience
- Published SMB pricing, rare in this category
- AI agent included from mid tiers
Zoho Analytics
Self-service BI with the Ask Zia assistant, at the category's friendliest prices.
- Cheapest serious entry point
- Part of the wider Zoho suite many SMBs use
- Spanish site and interface
Qlik
Full data platform with AI answers, priced per tenant rather than per user.
- Data pipeline and analytics in one
- AI answer agents from the entry tier
- Spanish site and long enterprise pedigree
Tableau
Salesforce's visual analytics standard, with Pulse pushing AI insights to you.
- The strongest visualisation craft in BI
- Pulse turns metrics into plain-language digests
- Massive community and learning resources
Off the shelf or custom?
When a platform is enough
If your data already sits somewhere connectable and your questions are the classic sales-margin-cash set, the platforms above are the right buy. Start where your stack points: Power BI in a Microsoft house, Zoho for tight budgets, ThoughtSpot when asking questions is the whole point.
When custom wins
Custom wins when the hard part is upstream of the chart: data scattered across systems that disagree, definitions that need untangling, or questions the platforms cannot reach. A custom layer, your data warehouse plus an AI interface tuned to your business terms, also wins when per-seat pricing across a whole company outgrows owning it.
Where Sabemos fits
Custom build
We build the layer that makes ask-your-data real: connecting the systems, agreeing the definitions, and an AI interface that speaks your business's vocabulary, in Spanish and English. Sometimes that ends in a custom assistant, sometimes in a platform configured properly on clean foundations.
Setup and onboarding
Choosing a platform? We implement it end to end: the connections, the data model, the metric definitions and the AI features configured, so the answers are ones your controller would sign.
Frequently asked questions
Can I trust the numbers it gives?
As much as the data and definitions underneath. The good platforms show their working, which makes errors visible. The real trust work is done before the AI: agreeing what revenue and margin mean and connecting the right sources.
Does my data go to the AI companies?
The mainstream BI platforms process your data under business terms and do not train public models on it. Where policy is strict, architectures exist that keep the data entirely in your environment; that is a design choice, not a blocker.
We live in Excel. Is that a problem?
No, it is the normal starting point. Spreadsheets can be sources, and the step up is making them feed one governed place instead of forty divergent copies.
What does this cost in practice?
Entry BI runs tens of euros per user monthly, with AI features sometimes an add-on or higher tier. A custom layer is a project cost that makes sense when seats multiply or the data work is the real problem.
How fast can we see something?
A pilot on one data source, one set of questions, takes days on any platform here. The full one-version-of-the-truth build takes weeks, mostly spent on definitions rather than software.