Capabilities
- Modern data stack design and implementation
- ETL/ELT pipelines and data modeling
- Dashboards, KPI design, and self-service analytics
- Data governance, quality, and observability
Approach
- Discovery: align metrics, sources, dimensions, and decisions
- Modeling: define semantic layer and conformed dimensions
- Engineering: build reliable ELT with tests and lineage
- Experience: deliver performant dashboards and semantic APIs
- Enablement: train teams and establish a data product mindset
Accelerators
- KPI catalog and governance starter kit
- Reusable dbt templates and CI checks
- Dashboard UX patterns and accessibility checklist
Platform & tools
- Azure Data Factory, Synapse, Fabric, Databricks
- SQL Server, Azure SQL, PostgreSQL, Snowflake
- dbt, Delta Lake, Lakehouse patterns
- Power BI, Tableau, Looker; Metrics Layer/semantic models
Sample deliverables
- BI roadmap and architecture
- dbt project with tests and docs
- Executive and operational dashboards
- Data quality and observability playbook
Outcomes
- Trusted metrics with clear ownership
- Faster insights and reduced ad-hoc reporting burden
- Lower cost-to-serve through standardization