Technology & Architecture
The categories of technology behind a Stratum Data platform.
Stratum Data designs and builds using the technology categories below, matched to each engagement's actual requirements — not a fixed stack applied everywhere regardless of fit.
Cloud Infrastructure
Compute and storage foundations that scale elastically with workload.
SQL & Python
The core languages behind transformation logic, orchestration, and analysis.
APIs
Structured interfaces for pulling and pushing data between systems.
ETL / ELT
Extraction, loading, and transformation patterns matched to the workload.
Streaming
Continuous data movement for near-real-time use cases.
Data Warehouses
Structured, query-optimized storage for analytical workloads.
Data Lakes
Flexible, large-scale storage for raw and semi-structured data.
Lakehouses
Combined lake flexibility with warehouse-grade query performance.
Containers
Portable, reproducible environments for pipeline and service deployment.
Infrastructure as Code
Version-controlled, repeatable infrastructure provisioning.
Workflow Orchestration
Scheduling, dependency management, and failure recovery for pipelines.
Observability
Monitoring, logging, and alerting across the data platform.
Governance in the Stack
Data governance runs through the architecture, not around it.
Access controls, classification, and lineage tracking are treated as core infrastructure requirements alongside compute and storage — not a separate layer added later.
Curious how this maps to your environment?
We'll walk through your current stack and where the gaps are.