Data Analysis and Business Intelligence
Having data isn't the same as having answers
Most companies don't lack data. They have data scattered across systems that don't talk to each other, reports that take three days to prepare, and meetings where every department presents different numbers for the same question.
The result is familiar: decisions get made on intuition, habit, or whoever speaks loudest. Not because information is missing, but because it arrives late, arrives scattered, or doesn't arrive at all.
Business Intelligence is the work of closing that gap. We consolidate your company's data sources, define the metrics that actually matter, and build dashboards and reports that answer business questions the moment they're asked.
Signs you need to structure your data
Every report is its own project
If preparing month-end numbers takes someone days, the process is consuming more value than it generates.
Numbers don't match across departments
Marketing has one sales figure, finance has another, sales has a third. None of them are wrong, each one just measures things differently.
Decisions wait for the data
When the answer to "how much did we sell by region this quarter?" takes a week, the decision has already been made without it.
Nobody's certain what's actually working
Money gets invested in channels, campaigns, or products without clear visibility into the return on each one.
The information lives in personal spreadsheets
Files with formulas only one person understands, saved on their own computer. An operational risk nobody accounts for.
Always looking backward
Reports explain what happened, but they don't help anticipate what comes next.
What We Do
Data Audit and Mapping
We identify what data exists, where it lives, who produces it, how reliable it is, and how frequently it's updated. This is the foundation of everything — and often the phase that reveals the first problems.
Source Consolidation and Integration
Connecting CRM, ERP, e-commerce platforms, marketing tools, analytics, invoicing systems, and spreadsheets. Data starts flowing into a single, automatically updated point.
Metric and KPI Definition
Before measuring, you need to decide what matters. We work with you to define indicators aligned with business objectives and, just as importantly, to agree on how each one is calculated. A shared definition eliminates half the arguments.
Dashboards
Visual panels that show the state of the business in real time, tailored to each profile: an executive view for management, an operational view for each team. The right information, for the right person, without the noise.
Automated Reports
Periodic reports generated and distributed automatically, always in the same format and at the same time. No more requesting them — they arrive on their own.
Marketing Performance Analysis
Results attributed by channel, campaign, and content. Cost per lead, customer acquisition cost, advertising ROI, and each touchpoint's real contribution to conversion.
Sales and Funnel Analysis
Conversion rates by stage, average sales cycle length, average customer value, performance by sales rep or region, and revenue forecasting based on the current pipeline.
Customer Analysis
Segmentation by behavior and value, retention and churn analysis, customer lifetime value, and identification of purchase patterns and cross-selling opportunities.
Predictive Analysis and Scenarios
When the data allows, models that anticipate trends, estimate demand, or identify customer churn risk, along with simulations that show the impact of different decisions.
Data Quality and Governance
Validation rules, inconsistency detection, and defined ownership for each data set. A dashboard is only useful if the numbers behind it are reliable.
How We Work
Questions before data
We start at the end: what decisions do you need to make, and what questions do you need to answer? A dashboard built from available data produces nice-looking charts. A dashboard built from the right questions produces decisions.
Source Audit
Assessment of what exists, in what condition, how reliable it is, and how well it can be integrated. In this phase, we identify gaps, data that would be needed but isn't yet being collected.
Data Model and Metrics
Defining the structure, calculation rules, and metrics glossary. Documented, so that the definition of each metric doesn't depend on anyone's memory.
Construction and Integration
Implementation of the collection, processing, and consolidation workflows. Development of dashboards and reports, with validation at each step against the numbers you already know.
Training and Adoption
A dashboard nobody opens is useless. We train teams to read, interpret, and actually use the information — and we adjust anything that isn't meeting real needs.
Continuous Evolution
Questions evolve as the business grows. We follow along, adjust indicators, and add new analyses as needs arise.
Information is available when it's needed, not three days after it's requested.
Who it's for?
Companies that already have enough operational volume for decisions to carry real consequences, and are still making them without structured information. That spend significant time preparing manual reports. That invest in marketing or sales channels without measuring returns rigorously. Or that have data scattered across multiple tools with no consolidated view of the business.
It's not a question of size. It's a question of complexity: once nobody can hold the whole business in their head, you need a system that can.
Let's talk about your processes?
An initial diagnosis identifies what information already exists, what's missing, and which dashboards would have immediate impact on decision-making.
Frequently Asked Questions
We often have little data. Does it still make sense?
Many times the problem isn't the quantity, it's the organization. And if data really is missing, the first step is defining what to start collecting — which is also part of this work.
What tools do you use?
It depends on the context, the volume of data, and the budget. We work with the leading BI and visualization platforms, and we prioritize solutions your team can maintain without permanent reliance on third parties.
How long does it take?
A dashboard focused on a single set of sources can be up and running within weeks. Projects involving integration of multiple systems and historical data cleanup take longer. We work in phases so value is delivered early.
What if our data is a mess?
It’s the most common scenario. It’s part of the job: cleaning, standardizing, and defining rules so the mess doesn’t happen again.
Does this replace Excel?
Not necessarily. Excel is still excellent for one-off and exploratory analysis. What it replaces is Excel as a recurring reporting system, where it becomes fragile, slow, and prone to errors.
Do we need to hire a data analyst?
Not always. A large part of the value lies in automating what is currently manual and structuring what is currently scattered. The need for dedicated roles appears, if at all, at a more advanced stage.
Who owns the data and the solutions?
You do. The entire structure, documentation, and access remain on your side.