Technology
The stack behind modern analytics.
Analytics depends on a layered set of technologies. The right choices depend on each organization's existing environment, scale, and skills — we are vendor-neutral by default.
Layer 1
Ingest
- APIs
- Structured interfaces for exchanging data between systems.
- ETL / ELT
- Extracting, loading, and transforming data into analytical form.
- Data pipelines
- Orchestrated, monitored workflows that run reliably on schedule.
Layer 2
Store
- Data warehouses
- Columnar stores optimized for analytical queries.
- Data lakes
- Low-cost storage for raw and semi-structured data.
- Cloud platforms
- Elastic compute and storage that scale with demand.
Layer 3
Analyze
- SQL
- The common language for querying and shaping data.
- Python
- Flexible analysis, automation, and modeling.
- Statistical modeling
- Rigorous methods for inference and estimation.
- Machine learning
- Models that learn patterns for prediction and classification.
Layer 4
Present
- Business intelligence
- Governed metrics and dashboards for ongoing monitoring.
- Data visualization
- Charts and graphics designed for accurate reading.
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