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Infrastructure Layer

Data Science

From complexity to clarity — insights powered by data science.

We build the data foundation your intelligence layer depends on — pipelines, warehouses, and analytics that are reliable, observable, and fast. From ingestion to executive dashboards, we make data an asset rather than a liability.

What you can expect

  • One trusted source of truth for metrics
  • Automated, observable data pipelines
  • Self-serve analytics for decision-makers
  • Data quality you can rely on

Capabilities

  • Data engineering & ELT pipelines
  • Cloud data warehousing & lakehouses
  • Business intelligence & dashboards
  • Statistical analysis & experimentation
  • Data quality & governance

Most analytics problems are plumbing problems

The dashboard nobody trusts is almost never a visualisation failure. It is two systems that define a customer differently, a pipeline that silently drops rows on a schema change, or a metric whose definition lives in one person's head. Until that is fixed, better charts only distribute the disagreement faster.

We start at the pipeline: tested, versioned transformations in dbt, a warehouse or lakehouse structured around how the business actually asks questions, and data-quality checks that fail loudly rather than degrade quietly. The reporting layer gets easy once the layer underneath is honest.

Decisions, not dashboards

A report earns its keep when someone changes a decision because of it. We work backwards from that: which decision, who makes it, how often, and what number would actually change their mind. Plenty of requested dashboards do not survive those four questions, and that is a cheap thing to discover early.

Where the question is causal rather than descriptive — did the change work, is the difference real — we set the experiment or statistical test up properly, because the alternative is an expensive decision made on a difference that was noise.