Data Analytics & Insights for Startups

Reports that people trust and actually use

Most organisations have more dashboards than they have people who trust them. Conflicting numbers between reports, metrics defined differently by different teams, data that is 24 hours stale by the time it reaches a dashboard, and BI tools that require SQL to answer any question not pre-built by engineering. We fix the underlying data infrastructure that causes these problems.

We build analytics stacks on the modern data stack: dbt for transformation and documented metric definitions, Snowflake or BigQuery as the analytical warehouse, and Looker, Metabase, or Power BI as the BI layer depending on your team's technical level and reporting requirements. Every metric is defined once in the semantic layer, not duplicated across dozens of individual reports.

Self-service analytics is the goal. We design data models and BI tooling so that analysts and business users can answer their own questions without an engineering ticket — while data governance controls prevent sensitive data from being inadvertently exposed and ensure metric definitions remain consistent.