What we do
We connect data sources, clean and model the data, and build dashboards, alerts, and reporting that support real decisions. The goal is to replace guesswork and spreadsheet chasing with trusted numbers.
Key Activities
- Audit data sources and define the ingestion plan
- Model business entities, KPIs, and reporting logic
- Build pipelines with performance, reliability, and observability in mind
- Optimize storage and queries for growing volume
- Deliver dashboards, reporting, and anomaly alerts
- Set data quality rules so people trust the output
Tech Focus
- ClickHouse, SQL Server, columnar and relational blends
- Python & Go for ingestion and transformation
- BI tools or embedded dashboards, depending on users
- Structured logging & metrics for pipeline observability
- Performance profiling & cost efficiency
Deliverables
- KPI definitions and data opportunity brief
- Canonical data model & storage specification
- Automated ingestion & transformation pipelines
- Executive dashboard pack (first version)
- Data quality rules & alerting baseline
- Operational metrics dashboard and runbooks
What this enables next
Once the data foundation is stable, the same system can support better planning, automation, and customer-facing reporting.
- Real-time visibility across sales, operations, and finance
- Retention, churn, and customer value analysis
- Forecasting for demand, cash flow, and capacity
- Automated alerts and workflow triggers
- Customer or partner dashboards and data feeds
Outcomes
One source of truth for key numbers, less manual reporting, faster decisions, and a cleaner base for future automation or product features.