Area 15 · Data, AI and consulting

Data and analytics

Monday, 9 a.m. at a small firm in Murcia: the office manager pulls sales out of Sage, opens the Amazon settlement, manually subtracts fees and carriage, then sends the directors a workbook. Meanwhile the sales lead has built his own sheet, with a different total. That routine swallows a few days every month and leaves two competing truths. We aim to leave you with one: tidy records, sources gathered in one place and dashboards that update without anybody touching them.

3
services in this area
1 figure
for sales, shared by every department
€75/h
+ VAT, or a fixed quote after diagnosis
EU
or Spain as the region where your data lives

Signs your data needs attention

Hardly anyone asks us to “clean master data”. They ask for a dashboard, and a look at the sources turns up one of these symptoms. Recognise two or more and the reporting tool is not where the trouble lies.

Meetings open with a row about the total

Definitions get written down. Sales counts by order date, accounts by invoice date, and credit notes are deducted differently by each.

Customers who exist three times

We clean up and set rules. “Talleres Ruiz”, “TALLERES RUIZ SL” and a record lacking an NIF count as three separate firms in any report.

Month-end drags on for a week

We automate the loads. Exporting, pasting and reconciling by hand ties up the person who knows the numbers best, right when they are needed most.

The stock report is two days old

We tune refresh frequency. When a product sells out faster than the report arrives, reordering becomes guesswork.

Delivery notes typed in at the warehouse

We set up automatic reading. Lines from Portuguese or Chinese suppliers are still copied into the ERP one at a time.

Nobody knows what each marketplace earns

We work out real channel margin. Amazon, Miravia and your own shop get compared on turnover, not on what is left after fees and returns.

A polished chart on dirty data is worse than an ugly spreadsheet. Whoever assembles the sheet by hand at least looks at the rows and sometimes spots nonsense. A slick dashboard radiates confidence, so nobody challenges it even when duplicates inflate active customers by a fifth. That is why we measure data quality before drawing anything, and we show you the error count as it is, without softening it.

From the Monday spreadsheet to a self-updating report

We begin with a single area, usually sales or stock, and a small set of measures. Other areas follow once the first report is in daily use. All of it is remote, through secure access to your systems and meetings on Teams or Google Meet.

01

A shared glossary

With accounts and sales we set down how revenue, margin, returns and an “active customer” are calculated. Skip this and the first report is disputed at its first outing.

02

Source map

ERP, shop, marketplaces, advertising and the unofficial spreadsheets. For each we note an owner, how it is accessed and which personal fields belong in the record of processing activities.

03

Parallel run

The first automated report runs next to the old spreadsheet for a few weeks. Every gap is explained before management retires the manual version.

04

Grow in layers

New areas and measures are added on the same model and loads, so each extra report costs noticeably less than the first.

Common questions

If you already run Microsoft 365 and Entra ID, Power BI fits naturally: permissions use the accounts you have and Excel stays one click away. Metabase, hosted on your own server, suits teams who would rather query PostgreSQL without a per-user licence. Both can read from the same warehouse. You see the full cost of each before choosing.

It should not. Reads happen overnight or in small batches, ideally through the program’s API or a database copy, never as heavy queries mid-morning. A separate warehouse exists for exactly this reason: dashboards query their own copy while whoever is invoicing in a3ERP notices nothing.

In an account held in your company’s name at OVHcloud, IONOS, Arsys or the Spanish regions of AWS or Azure, or on your own server if preferred. Our work is covered by a data processing agreement. Access follows roles: directors see everything, each sales rep sees their own territory. Views are logged, which makes answering your DPO straightforward.

Mostly that depends on the state of your master records. Reasonably clean data means an early first report, with most time spent agreeing definitions. Thousands of duplicates turn clean-up into the main project. So we give timescales after seeing your data, not at the first meeting. Work is fixed-price or €75 per hour + VAT within an agreed cap.

The Red.es Kit Digital programme includes categories for business intelligence and analytics, but grants are handled only through registered digitalisation agents, and Apply is not one. If you are considering the scheme, check the current terms on the official website. Our quotes do not rely on any subsidy.

Let us straighten out your numbers

Tell us which reports are still assembled by hand and where the figures disagree. We review the sources and suggest where to start.

Hours
Monday to Friday, 9:00-18:00 Spanish time (CET), answers within a working day
Meetings
Video calls via Google Meet or Teams

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