Data engineering, from raw data to decisions

Automated collection, ETL, enriched databases and dashboards: your company's scattered data in one place, updating on its own and ready to drive decisions.

Automated data collection from websites, APIs and public datasets, ETL pipelines, deduplication and enrichment, migration between platforms, geocoding and KPI dashboards connected to the company's systems.

What we deliver

  • Collection & Scraping
  • ETL & Pipelines
  • Geocoding
  • Dashboards & BI

Who it's for: Companies with data scattered across spreadsheets, systems and outside sources that need a single, up-to-date database

Why MData

  • Collection that runs itself: Collectors pull data from websites, APIs and public datasets on schedule, with checkpoints and a restart when a source goes down.
  • Data you can trust: Deduplication, validation and enrichment before any number reaches a dashboard.
  • From data to decisions: Dashboards, maps and reports that management actually uses every day, instead of spreadsheets nobody opens.

Frequently asked questions

What does data engineering involve?

It builds the path that takes data from where it starts to the people who use it: collection, cleanup, merging sources and loading it into a database or a dashboard. It's the work that comes before reports and AI. Without it, both show the wrong numbers.

Do you do web scraping?

Yes, from public sources and within each site's terms of use. The collectors run in parallel, respect rate limits and pick up where they left off when a source goes down. Personal data is only collected when there's a legal basis for it.

My data is in spreadsheets and in different systems. Can you bring it together?

Yes, and that's the most common case. We map each source, define the key that matches records across them and set up a load that runs on its own, without duplicating customers or products. The spreadsheet can stay, but it stops being the source of truth.

What is geocoding?

It's giving a piece of information coordinates so it shows up on a map: a customer's address, a lot in a subdivision, a delivery point. We also turn PDF site plans into polygons with area and coordinates, ready to cross-reference with the rest of your data.

What's the difference between MData and M-AI & ML?

MData takes care of the data: collecting it, cleaning it and keeping it in order. M-AI & ML uses that data to answer questions, automate tasks and predict outcomes. The two projects usually go together, with the same team.

Do you work with companies in Leme and the São Paulo countryside?

Yes. MFactor is based in Leme and works with companies in Pirassununga, Araras, Rio Claro, Limeira, Piracicaba, Campinas and all over Brazil. The work is remote, and when a project calls for meeting in person in the region, we come to you.

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