Services / Data Engineering
Service · Data EngineeringWe design, build, and run the platform where your data lives: replicated in real time, clean, modeled for the business, and governed by person, by department, and by client.
systems that didn't talk to each other, now a single source of truth: the numbers for all their clients, up to date and on one dashboard. Multi-client contact center.
Every system reports a different sales figure, and no one knows which one is right.
Data arrives late and by hand: every morning, someone exports it, pastes it, and forwards it.
Knowledge of the data rests with one or two people, and every business question has to go through them.
A central platform where all your data lives, organized in quality layers: from raw data to decision-ready numbers.
We bring in data from every system you already use, without stopping operations and, when needed, in real time.
Data is processed automatically every day, with checks so bad data doesn't make it into a report.
Tables are organized the way the business thinks (sales, customers, products), not the way each system stores them.
Every figure can be traced back to its source, and each person sees only what they're meant to see.
Your data, prepared so AI models and agents work with reliable information.
From scattered sources to a single source of truth: replication from every system, quality layers (bronze, silver, and gold), a model designed for the business, and governance that defines who can see each piece of data.
Real cases, described by industry. Client names are kept confidential.
They had no shared place to analyze their four databases. Today, all four are copied in real time to a single platform that refreshes every day and sets aside questionable data before it reaches a report. It's documented so another team can run it.
The team built and migrated the platforms where clinical data is processed, with automated processes that take it from raw to analysis-ready. It also aligned a 41-table model with an international clinical standard.
Their reports were built in spreadsheets. Today, their databases and applications feed a single platform, with a catalog of what it holds and permissions that define what each person sees.
Finding an inconsistency in their data took time. Today, automated rules check the quality of every table, and access to each piece of data is controlled.
Part of their operation lived in a NoSQL database (MongoDB) that couldn't be cross-referenced with the rest of their data. We replicated it in real time to SQL tables, alongside their relational databases, and today it flows into their reports and dashboards.
Within weeks, you know where the value is. From month one, you see it.
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