DatriseAI-first ETL

Kyriba to Looker Studio Integration

AI-first ETL from Kyriba into Looker Studio. Governed entities, incremental sync, typed landing tables.

How Datrise loads Kyriba into Looker Studio

Datrise syncs Kyriba's bank accounts, cash positions, payments, transactions, forecasts, and bank statements into Looker Studio as warehouse tables Looker Studio connects to. Flexible or custom fields land in flattened columns for chart fields, and timestamps such as created, updated, and status changes are typed as date dimension columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned tables to keep extract refresh fast. Looker Studio performs best on pre-aggregated tables, so Datrise lands tidy, report-shaped tables rather than raw API payloads.

Ideal for free, shareable dashboards on Google data sources.

Endpoints

Kyriba: Treasury, cash, and liquidity management.

Looker Studio: Google self-service dashboards and reporting (formerly Data Studio).

How Kyriba entities map to Looker Studio

Kyriba entityLooker Studio objectNotes
bank accountskyriba_bank_accountsid PK · custom fields → flattened columns for chart fields
cash positionskyriba_cash_positionsid PK · linked to kyriba_bank_accounts
paymentskyriba_paymentsid PK · linked to kyriba_bank_accounts
transactionskyriba_transactionsid PK · linked to kyriba_bank_accounts

FAQ

How does Datrise handle Kyriba's custom fields in Looker Studio?

Flexible values are stored as flattened columns for chart fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker Studio types.

How does the Kyriba to Looker Studio sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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