Built-in temporal operators, such as windowed aggregates, temporal joins, and temporal analytic functions. Native Azure input and output adapters Support for slow changing reference data (also known as a lookup tables), including joining with geospatial reference data for geofencing. Integrated solutions, such as Anomaly Detection Multiple time windows in the same query Ability to compose multiple temporal operators in arbitrary sequences.

Stream Analytics Query Language (SAQL)

The conditional split transformation routes data rows to different streams based on matching conditions. The conditional split transformation is similar to a CASE decision structure in a programming language.

disjoint is false because the data goes to the first matching condition.

Azure Blob Storage (JSON, Avro, Text, Parquet) Azure Data Lake Storage Gen1 (JSON, Avro, Text, Parquet) Azure Data Lake Storage Gen2 (JSON, Avro, Text, Parquet) Azure Synapse Analytics Azure SQL Database Azure CosmosDB

Use the flatten transformation to take array values inside hierarchical structures such as JSON and unroll them into individual rows. This process is known as denormalization.

Specify the start datetime of the trigger for Start Date. It's set to the current datetime in Coordinated Universal Time (UTC) by default.

When creating a schedule trigger, you specify a schedule (start date, recurrence, end date etc.) for the trigger, and associate with a pipeline. Pipelines and triggers have a many-to-many relationship. Multiple triggers can kick off a single pipeline. A single trigger can kick off multiple pipelines.

Specify Recurrence for the trigger. Select one of the values from the drop-down list (Every minute, Hourly, Daily, Weekly, and Monthly). Enter the multiplier in the text box. For example, if you want the trigger to run once for every 15 minutes, you select Every Minute, and enter 15 in the text box.

Azure Table storage is designed to store structured data.

PartitionKey: The PartitionKey property stores string values that identify the partition that an entity belongs to.

Table entities represent the units of data that are stored in a table. Table entities are similar to rows in a typical relational database table. Each entity defines a collection of properties. Each property is defined as a key/value pair by its name, value, and the value's data type.

Timestamp: The Timestamp property provides traceability for an entity.

RowKey: The RowKey property stores string values that uniquely identify entities within each partition. The PartitionKey and the RowKey together form the primary key for the entity.