ELT for financial services
Consolidate transactions, strengthen controls, and ship reporting pipelines with Skippr Cloud ELT. Exactly-once delivery, streaming sources, and a runner you operate.
See ELT product and Install.
The data problem
| Challenge | What you see |
|---|---|
| Split systems | Core banking, payments, CRM, and ledgers each hold a slice of the customer journey. |
| Regulatory reporting | Controls and reproducible reporting are required; ad hoc extracts do not scale. |
| Near-real-time analytics | Fraud, risk, and product teams need events in the warehouse as they arrive. |
How Skippr Cloud ELT helps
- WAL-backed exactly-once delivery for reconciliation. See Features.
- Stream events into the warehouse. See CDC and CDC overview.
- Generate documented dbt marts for reporting. See Data modeling.
Sources teams use
- PostgreSQL — hub: PostgreSQL
- MSSQL — hub: MSSQL
- Kafka — hub: Kafka
- DynamoDB — hub: DynamoDB
- S3 — hub: S3
Warehouses
- Snowflake — hub: Snowflake
- BigQuery — hub: BigQuery
- Databricks — hub: Databricks
Compliance
- Design pipelines with SOX and PCI-DSS in mind; the runner does not replace your control framework.
- Self-hosted deployment keeps source data on the path you configure.
- dbt models in git give an audit trail for transforms.