DatriseAI-first ETL

Sierra Interactive Azure Data Lake Storage

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

How Datrise loads Sierra Interactive into Azure Data Lake Storage

Datrise syncs Sierra Interactive's contacts, accounts, deals, activities, and lifecycle events 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

Sierra Interactive: Real estate CRM for leads, listings, and agent follow-up.

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

How Sierra Interactive entities map to Azure Data Lake Storage

Sierra Interactive entityAzure Data Lake Storage objectNotes
contactssierra_interactive_contactsid PK · custom fields → nested struct/map fields in Parquet
accountssierra_interactive_accountsid PK · linked to sierra_interactive_contacts
dealssierra_interactive_dealsid PK · linked to sierra_interactive_contacts
activitiessierra_interactive_activitiesISO-8601 timestamp columns events

FAQ

How does Datrise handle Sierra Interactive'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 Sierra Interactive 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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