Data & Analytics Competency
Validated for warehouses, streaming pipelines, and managed ETL that stay operable after the engineering team leaves.
- Validated
- January 2026
- January 2028
- 2 submitted
What it covers
Modelled from decisions backward.
The common failure is a technically correct warehouse nobody queries. Validation examines modelling discipline, data quality practice, and whether the platform is actually used.
Dimensional modelling
Facts and dimensions designed for the query patterns that follow.
Pipelines
Batch and streaming ingest, orchestrated with dependency-aware retries.
Data quality
Assertions on volume, freshness, and nulls that fail the load, not the report.
Self-serve BI
A semantic layer so two dashboards cannot disagree on a metric.
Validation criteria
What AWS assessed.
Data & Analytics validation required evidence of production pipelines under real load, plus demonstrated client adoption of the resulting platform.
How validation worksProduction pipelines
Ingest and transformation running at volume with monitoring in place.
Modelling review
Warehouse schemas examined against query patterns and governance needs.
Adoption evidence
Named business users querying the platform without engineering support.
Cost modelling
Warehouse run cost projected and validated against actual spend.
Evidence
The engagements behind it.
These are the customer references submitted to AWS for this competency. Ask us about any of them.
Sub-second
Telemetry latency
Route analytics and live dispatch
Kinesis ingest through Redshift modelling, with dispatcher dashboards fed from the stream.
1 → 50
Branches supported
Merchant analytics for Mercado
Multi-location inventory and sales analytics modelled for merchants scaling from one shop to a chain.
Architecture
Patterns behind this practice.
Services
What we build it on.
- Redshift
- Kinesis
- Glue
- Athena
- S3
- QuickSight
- Step Functions
Team on this practice
Data engineering sits inside the main bench — the same people build venture analytics and client warehouses.
Other competencies.
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Work with this practice
Building a platform people will query?
Discovery comes first — a short, bounded review that ends in an architecture, a scope, and a price. You keep the output either way.