You create an important report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. You notice that visualizations are not showing data that is less than 1 hour old. What should you do?

• A.Disable caching by editing the report settings.
• B.Disable caching in BigQuery by editing table details.
• C.Refresh your browser tab showing the visualizations.
• D.Clear your browser history for the past hour then reload the tab showing the virtualizations.

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You are designing storage for very large text files for a data pipeline on Google Cloud. You want to support ANSI SQL queries. You also want to support compression and parallel load from the input locations using Google recommended practices. What should you do?

• A.Transform text files to compressed Avro using Cloud Dataflow. Use BigQuery for storage and query.
• B.Transform text files to compressed Avro using Cloud Dataflow. Use Cloud Storage and BigQuery permanent linked tables for query.
• C.Compress text files to gzip using the Grid Computing Tools. Use BigQuery for storage and query.
• D.Compress text files to gzip using the Grid Computing Tools. Use Cloud Storage, and then import into Cloud Bigtable for query.

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To run a TensorFlow training job on your own computer using Cloud Machine Learning Engine, what would your command start with?

• A.gcloud ml-engine local train
• B.gcloud ml-engine jobs submit training
• C.gcloud ml-engine jobs submit training local
• D.You can't run a TensorFlow program on your own computer using Cloud ML Engine .

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You are designing storage for 20 TB of text files as part of deploying a data pipeline on Google Cloud.
Your input data is in CSV format. You want to minimize the cost of querying aggregate values for multiple users who will query the data in Cloud Storage with multiple engines. Which storage service and schema design should you use?

• A.Use Cloud Bigtable for storage. Link as permanent tables in BigQuery for query.
• B.Use Cloud Bigtable for storage. Install the HBase shell on a Compute Engine instance to query the Cloud Bigtable data.
• C.Use Cloud Storage for storage. Link as permanent tables in BigQuery for query.
• D.Use Cloud Storage for storage. Link as temporary tables in BigQuery for query.

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Which Cloud Dataflow / Beam feature should you use to aggregate data in an unbounded data source every hour based on the time when the data entered the pipeline?

• A.An hourly watermark
• B.An event time trigger
• C.The with Allowed Lateness method
• D.A processing time trigger

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