Data Analytics & Business Intelligence
What we do
Most analytics projects fail at definition, not implementation. Teams build dashboards before agreeing on what the numbers mean, then spend months reconciling conflicting reports. We start with metric alignment - working with leadership to define exactly what gets measured, how it gets calculated, and where it gets surfaced. From there we build the warehouse, transformation layer, semantic models, and dashboards as one integrated system. The result is a platform your team uses daily because the data is fresh, the definitions are consistent, and the answers are immediate.
Data Warehousing & Transformation
Snowflake, BigQuery, and Databricks implementations with dbt-managed transformation pipelines. Clustering, partitioning, and cost controls configured for your query patterns and data volume. Version-controlled SQL, automated testing, and documentation for every model.
Executive & Operational Dashboards
Dashboard hierarchies that serve board-level summaries, departmental views, and individual contributor metrics from one source of truth. Embedded analytics for SaaS products using iframe embedding or React components with tenant isolation and design system theming.
Automated Reporting & Alerts
Conditional reports and KPI breach alerts delivered to the right person with enough context to act immediately. Reverse ETL pipelines push analytics back into CRMs, marketing platforms, and support tools - closing the loop between insight and action.
How we work together
Metric Definition & Data Audit
We interview stakeholders across product, operations, and finance to define the metrics that drive decisions. We map existing data sources, assess quality and freshness, and document the gap between available data and required analytics. Deliverables include a metric dictionary, data catalogue, and analytics requirements specification.
Warehouse Architecture & Transformation
Data warehouse implementation on Snowflake, BigQuery, or Databricks with dimensional modelling using dbt. We build staging, intermediate, and mart layers that separate raw ingestion from business logic, with automated tests, lineage tracking, and access controls at every layer.
Semantic Layer & Dashboard Development
A semantic layer using LookML, dbt metrics, or Cube translates warehouse tables into business-friendly dimensions and measures. Dashboards built in Looker, Metabase, or Preset load in under three seconds, with progressive disclosure that gives executives the summary and analysts the drill-down.
Reporting Automation & Adoption
Scheduled reports via email, Slack, or Teams with threshold-based alerts that surface exceptions before anyone asks. We track dashboard usage to identify which views drive decisions and which get ignored, then iterate based on adoption patterns. Documentation and training ensure the platform is self-serve.