Ingest and process the data — Professional Data Engineer

The official GCP documentation our Ingest and process the data practice questions are cited to. Review the primary sources, then practise.

Official references for this objective

Google Cloud — Dataflow: streaming analytics | Google Cloud

Straggler detection automatically identifies performance bottlenecks, while data sampling allows observing data at each pipeline step.
Google Cloud — Pub/Sub for Application & Data Integration | Google Cloud

Dead letter topics allow for messages unable to be processed by subscriber applications to be put aside
Google Cloud — Managed Service for Apache Spark (formerly Dataproc) | Google Cloud

Migrating legacy Spark or OSS workloads, running persistent clusters, or requiring deep open-source customization. Cluster uptime
Google Cloud — Batch: Simplicity for Batch Computing | Google Cloud

Provisions and autoscales capacity while eliminating the need to manage third-party solutions
Google Cloud — Change Data Capture | Google Cloud

Serverless platform that automatically scales, with no resources to provision or manage
Google Cloud — Cloud Data Fusion | Google Cloud

Broad library of 150+ preconfigured connectors and transformations , at no additional cost
Google Cloud — Managed Service for Apache Airflow | Apache Airflow 3

A fully managed workflow orchestration service built on Apache Airflow.
Google Cloud — Storage Transfer Service | Google Cloud

Complete transfers without writing a single line of code Centralized job management to monitor transfer status
Google Cloud — Workflows | Google Cloud

Wait up to one year Wait for a given period to implement polling.