Public works wants an incremental load of streetlight outages managed as a pipeline with declarative table definitions. What should they create?
Select an answer to reveal the explanation.
Short Explanation
A declarative pipeline is the streetlight work-order conveyor—define the tables and it keeps loading outages incrementally. A Databricks Jobs pipeline workflow with declarative tasks for streetlight outages isn't the declarative managed pipeline you need, so it won't give you declarative table definitions. You'll see a standard pipeline view with declarative SQL doesn't actually store data and an Auto Loader ingestion pipeline with declarative tables isn't a managed declarative pipeline by itself, so they're not what you're asked for.
Full Explanation
Public works wanting an incremental load of streetlight outages managed as a pipeline with declarative table definitions should create a Lakeflow Spark Declarative Pipeline. Declarative pipelines define tables and incremental semantics as a managed graph—fitting municipal outage ingest that must load incrementally rather than relying on a Databricks Jobs pipeline workflow with declarative tasks for streetlight outages, which orchestrates tasks rather than defining managed declarative tables. Declarative definitions plus incremental processing are the combined requirement for a maintainable outage pipeline.
A Databricks Jobs pipeline workflow with declarative tasks for streetlight outages orchestrates tasks rather than defining declarative tables and lacks the managed incremental graph the requirement calls for. A Unity Catalog standard pipeline view with declarative SQL for streetlight outages fails the declarative pipeline ask because it is a read-only query object, not a managed pipeline that incrementally loads and stores data, and it is hard to operate on-call for outage ingest. An Auto Loader ingestion pipeline with declarative tables for streetlight outages is not the declarative pipeline construct the question asks for; it incrementally reads files as a source but does not by itself provide the managed declarative pipeline graph.
Exam caveat: Lakeflow Spark Declarative Pipelines are the exam’s declarative incremental pipeline construct—a Unity Catalog standard pipeline view with declarative SQL for streetlight outages does not actually load or store data and is not the production answer when the question asks for a managed declarative incremental pipeline. Operational check: define a declarative pipeline that incrementally ingests streetlight outages into bronze and silver tables, run an update with new outage files, confirm only new or changed data is processed as designed, set expectations for data quality, and monitor pipeline runs.
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