DatriseAI-first ETL

CSV File to Domo Integration

AI-first ETL from CSV File into Domo. Governed entities, incremental sync, typed landing tables.

How Datrise loads CSV File into Domo

Datrise syncs CSV File's rows, columns, headers, delimiters, file batches, and encodings into Domo as datasets in Domo's cloud store via connector. Flexible or custom fields land in flattened columns for Magic ETL, and timestamps such as created, updated, and status changes are typed as date/time columns.

Sync is incremental: Datrise uses partitioned dataset updates rather than full replaces, so re-runs update only what changed. Domo dataset partitions keyed on load date. Domo stores its own copy of data, so Datrise sends incremental partitions to avoid re-uploading whole datasets.

Ideal for all-in-one cloud BI with built-in ETL.

Endpoints

CSV File: Delimited flat files from exports and drops.

Domo: Cloud BI platform combining data integration and executive dashboards.

How CSV File entities map to Domo

CSV File entityDomo objectNotes
rowscsv_file_rowsid PK · custom fields → flattened columns for Magic ETL
columnscsv_file_columnsid PK · linked to csv_file_rows
headerscsv_file_headersid PK · linked to csv_file_rows
delimiterscsv_file_delimitersid PK · linked to csv_file_rows

FAQ

How does Datrise handle CSV File's custom fields in Domo?

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

How does the CSV File to Domo sync stay up to date?

It runs incrementally — Datrise uses partitioned dataset updates rather than full replaces.

Related pipelines

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