Data Analytics & Business Intelligence
Numbers your leadership team will actually use.
We build the data infrastructure and analytics that let your business answer questions in minutes — not weeks.
What this means
In plain terms.
Data warehouse design, ETL/ELT pipelines, dbt models, BI dashboards, self-serve analytics, embedded reporting. We build the stack and train your team to run it.
A predictable path from intent to launch.
Six phases, repeated on every engagement — calibrated to your scale, never improvised.
Phase 1
Questions worth asking
Map decisions to data needs.
Phase 2
Source audit
Inventory existing data sources and gaps.
Phase 3
Warehouse design
Star/snowflake schemas, dimensional modeling.
Phase 4
Pipelines
Ingestion, transformation, quality monitoring.
Phase 5
Dashboards
Executive, operational, embedded views.
Phase 6
Enablement
Train your analysts. Hand over with confidence.
Technologies
The stack, chosen with intent.
We pick tools because they fit the problem, not because they trend on Hacker News. Below are the ones we reach for most often.
- BigQuery
- Snowflake
- Redshift
- dbt
- Airflow
- Metabase
- Looker
- PowerBI
Why us, specifically
What makes our version different.
Dimensional modeling — your data warehouse stays sane at scale.
Data quality monitoring on every pipeline.
Dashboards executives open daily, not once a quarter.
We train your team to maintain it.
The questions our prospects ask, answered.
BigQuery if you are on GCP or have unpredictable workloads. Snowflake for predictable enterprise workloads.
PII tagging, row-level security, column masking, audit logs.
When needed — Kafka, Materialize, Flink. Most BI is near-real-time, which is much cheaper.
Yes — Cube.js, Metabase embedding, custom React dashboards.
Often yes — see our AI & ML service.