Event-driven architecture (EDA) is a common data integration pattern that involves production, detection, consumption, and reaction to events. Data integration scenarios often require Data Factory customers to trigger pipelines based on events happening in storage account, such as the arrival or deletion of a file in Azure Blob Storage account. Data Factory natively integrates with Azure Event Grid, which lets you trigger pipelines on such events.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-event-trigger
https://docs.microsoft.com/en-us/azure/data-factory/concepts-pipeline-execution-triggers

Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-use-reference-data

Reference:
https://docs.microsoft.com/en-us/azure/data-factory/source-control

The Delta provides the ability to infer the schema for data input which further reduces the effort required in managing the schema changes. The Slowly Changing Data(SCD) Type 2 records all the changes made to each key in the dimensional table. These operations require updating the existing rows to mark the previous values of the keys as old and then inserting new rows as the latest values. Also, Given a source table with the updates and the target table with dimensional data, SCD Type 2 can be expressed with the merge.
Example:
// Implementing SCD Type 2 operation using merge function
customersTable
.as("customers")
.merge(
stagedUpdates.as("staged_updates"),
"customers.customerId = mergeKey")
.whenMatched("customers.current = true AND customers.address <> staged_updates.address")
.updateExpr(Map(
"current" -> "false",
"endDate" -> "staged_updates.effectiveDate"))
.whenNotMatched()
.insertExpr(Map(
"customerid" -> "staged_updates.customerId",
"address" -> "staged_updates.address",
"current" -> "true",
"effectiveDate" -> "staged_updates.effectiveDate",
"endDate" -> "null"))
.execute()
}
Reference:
https://www.projectpro.io/recipes/what-is-slowly-changing-data-scd-type-2-operation-delta-table-databricks

Reference:
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-secure-data