DatriseAI-first ETL

Mambu to ThoughtSpot Integration

AI-first ETL from Mambu into ThoughtSpot. Governed entities, incremental sync, typed landing tables.

How Datrise loads Mambu into ThoughtSpot

Datrise syncs Mambu's clients, loan accounts, deposit accounts, transactions, repayments, and products into ThoughtSpot as warehouse tables ThoughtSpot indexes for search. Flexible or custom fields land in flattened columns for searchable fields, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses incremental refresh of the indexed tables, so re-runs update only what changed. Date-partitioned facts for live-query performance. ThoughtSpot search relies on clear names and relationships, so Datrise lands well-named, joinable tables.

Ideal for natural-language search analytics over a warehouse.

Endpoints

Mambu: Cloud core banking and lending engine.

ThoughtSpot: Search-driven analytics with AI-assisted insights on warehouse data.

How Mambu entities map to ThoughtSpot

Mambu entityThoughtSpot objectNotes
clientsmambu_clientsid PK · custom fields → flattened columns for searchable fields
loan accountsmambu_loan_accountsid PK · linked to mambu_clients
deposit accountsmambu_deposit_accountsid PK · linked to mambu_clients
transactionsmambu_transactionsid PK · linked to mambu_clients

FAQ

How does Datrise handle Mambu's custom fields in ThoughtSpot?

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

How does the Mambu to ThoughtSpot sync stay up to date?

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

Related pipelines

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