DatriseAI-first ETL

Dixa Redash

AI-first ETL from Dixa into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Dixa into Redash

Datrise syncs Dixa's conversations, agents, customers, tags, and resolution metrics into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Dixa: Customer service platform for conversations across channels.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Dixa entities map to Redash

Dixa entityRedash objectNotes
conversationsdixa_conversationsid PK · custom fields → flattened columns for query results
agentsdixa_agentsid PK · linked to dixa_conversations
customersdixa_customersid PK · linked to dixa_conversations
tagsdixa_tagsid PK · linked to dixa_conversations

FAQ

How does Datrise handle Dixa's custom fields in Redash?

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

How does the Dixa to Redash sync stay up to date?

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

Related pipelines

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