DatriseAI-first ETL

Day.ai to Azure Data Lake Storage Integration

AI-first ETL from Day.ai into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.

How Datrise loads Day.ai into Azure Data Lake Storage

Datrise syncs Day.ai's contacts, companies, meetings, opportunities, AI summaries, and relationship signals into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.

Ideal for Azure lakehouse storage shared across Synapse and Databricks.

Endpoints

Day.ai: CRM that builds records from meetings and email automatically.

Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.

How Day.ai entities map to Azure Data Lake Storage

Day.ai entityAzure Data Lake Storage objectNotes
contactsday_ai_contactsid PK · custom fields → nested struct/map fields in Parquet
companiesday_ai_companiesid PK · linked to day_ai_contacts
meetingsday_ai_meetingsid PK · linked to day_ai_contacts
opportunitiesday_ai_opportunitiesid PK · linked to day_ai_contacts

FAQ

How does Datrise handle Day.ai's custom fields in Azure Data Lake Storage?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Data Lake Storage types.

How does the Day.ai to Azure Data Lake Storage sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.

Related pipelines

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