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Free sample question, answered and explained below. The Associate Data Practitioner practice bank has 1,132 more like it. Try 10 free: instant score, no account.
A data analytics team is designing a transformation pipeline to process large volumes of unstructured image data. The pipeline requires intensive linear algebra and numeric matrix computations for feature extraction before the processed metrics are loaded into BigQuery. The team needs a processing engine that supports specialized hardware acceleration (GPUs) to maximize execution performance.
Which Google Cloud product should the team choose to implement this transformation pipeline?
Application Integration is an Integration-Platform-as-a-Service (iPaaS) solution in Google Cloud designed to connect enterprise SaaS applications, trigger business events, and coordinate API workflows between systems like Salesforce, ServiceNow, and Jira.
The requirement was to build an event-driven workflow that connects customer relationship management (CRM) systems and webhooks to trigger downstream cloud tasks upon specific business events.
BigQuery scheduled SQL queries are recurring SQL jobs configured to run analytical SQL queries on tables residing directly inside BigQuery, typically used for periodic aggregation, table appending, and ELT transformations.
The pipeline operated entirely on existing tabular structured data inside BigQuery and needed scheduled SQL statements to aggregate daily transaction totals.
Cloud Dataflow is a fully managed, serverless stream and batch data processing service based on the open-source Apache Beam SDK. It enables large-scale parallel processing of structured, semi-structured, and unstructured data while dynamically provisioning worker compute resources.
When transformation complexity involves unstructured files, heavy mathematical operations, and specialized hardware acceleration requirements, Dataflow is Google Cloud's primary managed processing engine capable of running distributed GPU-accelerated pipelines.
BigQuery Data Transfer Service (DTS) is a fully managed scheduling service that automates data movement into BigQuery from Software-as-a-Service (SaaS) applications (such as Google Ads, YouTube, and Google Play) and cloud storage locations on a scheduled basis.
The scenario required setting up an automated, recurring schedule to ingest standard log files or external SaaS application metrics from Cloud Storage into BigQuery tables without performing any custom numeric transformations.
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