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Data Engineering & Analytics

Clean data before trusted dashboards.

The database gets cleaned before the dashboard gets trusted — pipelines that normalize your data on a schedule, not a one-time favor.

If the data is dirty, every model built on it is too.

Most reporting problems are not reporting problems — they are unnormalized source data pretending to be a metric. We start by cleaning and normalizing the databases feeding your dashboards, then build the ETL and ELT pipelines that keep them clean on a schedule, not a one-time favor. Server-side conversion tracking replaces the browser-side tags that ad blockers and cookie policies are steadily breaking, so a conversion is recorded once, correctly, and tied to the channel that actually earned it. On top of that we build attribution models that hold up across multi-touch journeys, so budget moves toward what the data shows working, not what a last-click report guessed.

1
Source-of-truth schema per metric, version-controlled instead of buried in a query
100%
Conversions tracked server-side, immune to ad-blocker and cookie loss
0
Manual CSV exports required once the pipeline is live
How we work

The engagement

Audit

Map every data source and every place two systems already disagree about the same number, before writing a line of transformation logic.

Normalize

Design the schema and build the ETL and ELT pipelines that turn inconsistent sources into one normalized reporting layer, in version control.

Track

Wire server-side conversion tracking and attribution modeling directly to revenue events, not to a pixel that a browser might block tomorrow.

Ship

Hand over documented, version-controlled pipelines and a reporting layer your team can trust without asking anyone to export a spreadsheet.

Let's turn your growth into a system.