Which activity is not performed with authoring Streaming Insights via SQL?

• A. Mapping to real-time sources
• B. Using Data Actions
• C. Creating timestamps in Data Cloud
• D. Scheduling periodic reports

Answer: (C)

Streaming Insights via SQL is about defining real-time processing of streaming data and driving immediate actions from those insights. You connect to live sources and set up SQL-based queries that run continuously, then use those results to trigger Data Actions in real time. The activity of mapping to real-time sources is a fundamental step here, since you need to know where the streaming data comes from. Data Actions are also a natural fit, enabling automated responses as soon as an insight is produced.

Creating timestamps in Data Cloud, however, isn’t something you typically do during authoring Streaming Insights with SQL. Timestamps usually come from the event data itself or are assigned at ingestion by the processing layer; they aren’t something you generate anew through the SQL-based streaming insight authoring process. If you need a timestamp, you rely on the source-provided event time or a processing-time marker rather than creating a new timestamp value within the streaming SQL authoring workflow. Scheduling periodic reports is more aligned with batch or offline reporting, which is separate from real-time streaming insights, so it isn’t the core activity in authoring streaming insights via SQL.