Solution
Data & BI
We turn information into decisions.
Overview
What we do
We integrate, clean and model your data, and turn it into dashboards and KPIs that steer the business.
We choose tools to fit your goal — not the other way around. Engineering over technology trends.
Capabilities
Concrete capabilities.
Data engineering and ETL
Integration, cleaning, migration and data modeling.
Data Warehouse and Data Lake
A single source of truth to analyze with confidence.
Business Intelligence
Executive dashboards with Power BI, Tableau and Looker.
Predictive analytics
Models that anticipate demand, risk and opportunity.
Use cases
Where it applies.
- Real-time executive dashboard
- Unifying scattered data
- Automated KPIs and reports
FAQ
Frequent questions.
What if my data is messy?
We start with quality: cleaning, normalization and modeling before analysis.
Which BI tool do you use?
Whichever fits you best: Power BI, Tableau or Looker Studio.
What is the difference between data engineering and BI?
Data engineering integrates, cleans and models your data into a single reliable source; BI takes that base and turns it into dashboards and KPIs to decide. You need both: without clean data, a pretty dashboard shows wrong conclusions.
What do cost and time depend on?
On how many data sources must be integrated, the state of that data and the complexity of the reports. A dashboard over already-clean data ships fast; consolidating scattered, messy sources takes more upfront work.
Do I need a Data Warehouse or is a dashboard enough?
It depends on volume and how many sources you cross. If it is little data from a single source, connecting a dashboard directly sometimes suffices; when you integrate many sources and want a single truth, a Data Warehouse or Data Lake is justified.
Can the dashboards be real-time?
Yes, depending on the source and how often the data updates. We design anything from reports that refresh daily to real-time boards, balancing the real need against the cost of maintaining them.
What is predictive analytics and when is it useful?
It is using your historical data to anticipate demand, churn risk or opportunities. It works when you have enough quality history; if your data is still scattered or dirty, we fix that first.
What technologies do you use for data?
ETL processes to integrate and clean, PostgreSQL and Data Warehouse or Data Lake architectures as a source of truth, and Power BI, Tableau or Looker Studio to visualize. We choose based on your volume and your team.
How do we start?
With an assessment of your data sources and the decisions you want to make; from there comes what to integrate and what to measure first. Write to [email protected].
Ready to start?
Tell us about your challenge and we’ll shape the right solution.