GCP · objective · 20% of the exam
Ingest and process the data
Exam objectives are the official skill domains Professional Data Engineer tests. Below are the official GCP docs our questions on this objective cite — review them, then practise.
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Official references for this objective
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Google Cloud — Dataflow: streaming analytics | Google Cloud
Straggler detection automatically identifies performance bottlenecks, while data sampling allows observing data at each pipeline step.
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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
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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
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Google Cloud — Batch: Simplicity for Batch Computing | Google Cloud
Provisions and autoscales capacity while eliminating the need to manage third-party solutions
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Google Cloud — Change Data Capture | Google Cloud
Serverless platform that automatically scales, with no resources to provision or manage
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Google Cloud — Cloud Data Fusion | Google Cloud
Broad library of 150+ preconfigured connectors and transformations , at no additional cost
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Google Cloud — Managed Service for Apache Airflow | Apache Airflow 3
A fully managed workflow orchestration service built on Apache Airflow.
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Google Cloud — Storage Transfer Service | Google Cloud
Complete transfers without writing a single line of code Centralized job management to monitor transfer status
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Google Cloud — Workflows | Google Cloud
Wait up to one year Wait for a given period to implement polling.