Mambu to GoodData Integration
AI-first ETL from Mambu into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Mambu into GoodData
Datrise syncs Mambu's clients, loan accounts, deposit accounts, transactions, repayments, and products into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
Mambu: Cloud core banking and lending engine.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Mambu entities map to GoodData
| Mambu entity | GoodData object | Notes |
|---|---|---|
| clients | mambu_clients | id PK · custom fields → flattened columns |
| loan accounts | mambu_loan_accounts | id PK · linked to mambu_clients |
| deposit accounts | mambu_deposit_accounts | id PK · linked to mambu_clients |
| transactions | mambu_transactions | id PK · linked to mambu_clients |
FAQ
How does Datrise handle Mambu's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the Mambu to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
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Early access
Connect Mambu to GoodData the easy way
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