Free Google Associate-Data-Practitioner Exam Dumps Questions & Answers

You have an existing weekly Storage Transfer Service transfer job from Amazon S3 to a Nearline Cloud Storage bucket in Google Cloud. Each week, the job moves a large number of relatively small files. As the number of files to be transferred each week has grown over time, you are at risk of no longer completing the transfer in the allocated time frame. You need to decrease the total transfer time by replacing the process.
Your solution should minimize costs where possible. What should you do?

• A.Create a transfer job using the Google Cloud CLI, and specify the Standard storage class with the - custom-storage-class flag.
• B.Create a batch Dataflow job that is scheduled weekly to migrate the data from Amazon S3 to Cloud Storage.
• C.Create an agent-based transfer job that utilizes multiple transfer agents on Compute Engine instances.
• D.Create parallel transfer jobs using include and exclude prefixes.

Your company is setting up an enterprise business intelligence platform. You need to limit data access between many different teams while following the Google-recommended approach. What should you do first?

• A.Create a separate Looker Studio report for each team, and share each report with the individuals within each team.
• B.Create a Looker (Google Cloud core) instance, and configure different Looker groups for each team.
• C.Create one Looker Studio report with multiple pages, and add each team's data as a separate data source to the report.
• D.Create a Looker (Google Cloud core) instance, and create a separate dashboard for each team.

You want to process and load a daily sales CSV file stored in Cloud Storage into BigQuery for downstream reporting. You need to quickly build a scalable data pipeline that transforms the data while providing insights into data quality issues. What should you do?

• A.Load the CSV file as a table in BigQuery, and use scheduled queries to run SQL transformation scripts.
• B.Load the CSV file as a table in BigQuery. Create a batch pipeline in Cloud Data Fusion by using a BigQuery source and sink.
• C.Create a batch pipeline in Dataflow by using the Cloud Storage CSV file to BigQuery batch template.
• D.Create a batch pipeline in Cloud Data Fusion by using a Cloud Storage source and a BigQuery sink.

You manage data at an ecommerce company. You have a Dataflow pipeline that processes order data from Pub/Sub, enriches the data with product information from Bigtable, and writes the processed data to BigQuery for analysis. The pipeline runs continuously and processes thousands of orders every minute. You need to monitor the pipeline's performance and be alerted if errors occur. What should you do?

• A.Use the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.
• B.Use Cloud Monitoring to track key metrics. Create alerting policies in Cloud Monitoring to trigger notifications when metrics exceed thresholds or when errors occur.
• C.Use BigQuery to analyze the processed data in Cloud Storage and identify anomalies or inconsistencies.
  Set up scheduled alerts based when anomalies or inconsistencies occur.
• D.Use Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.

Your company has several retail locations. Your company tracks the total number of sales made at each location each day. You want to use SQL to calculate the weekly moving average of sales by location to identify trends for each store. Which query should you use?

• A.
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• D.