Google Professional Data Engineer
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You are tasked with preparing ads data for AI models and historical analytics, where identifying longtail and outlier data points is crucial. The data requires near-real-time cleansing before AI model usage. Which approach should you adopt for data cleansing?
A
Utilize Cloud Composer to pinpoint longtail and outlier data points, then export a clean dataset to BigQuery.
B
Employ Dataflow for programmatic identification of longtail and outlier data points, using BigQuery as the destination.
C
Leverage BigQuery for data ingestion, preparation, and analysis, followed by query execution to generate views.
D
Adopt Cloud Storage as a data warehouse, process data with shell scripts, and use BigQuery to create dataset views.