Data & Analytics
Big Data Integration
Pipelines that bring scattered sources into one warehouse you can actually query.
What we usually find
The data exists, in nine systems, in four formats, with three different definitions of customer. Every question turns into a two-week project.
What the work covers
Scope is agreed in writing before anything starts. If a line here is not relevant to you, it comes out of the plan and out of the price.
- Source inventory with ownership and refresh expectations
- Ingestion pipelines with schema evolution handled
- Modelled warehouse layer with tested transformations
- Data quality checks that fail loudly rather than silently
- Lineage documentation from source column to final report
Typical tooling
Indicative, not fixed. The stack follows your constraints and your team, not our habits.
- dbt
- Airflow
- BigQuery
- Snowflake
- Python
More in Data & Analytics
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Need Big Data Integration?
Bring us the problem rather than a spec. We will tell you what it takes, what it costs, and what we would leave out.