Latest Google Associate-Data-Practitioner Actual Free Exam Questions & Community Discussion, Page 6

Question #51

You manage a web application that stores data in a Cloud SQL database. You need to improve the read performance of the application by offloading read traffic from the primary database instance. You want to implement a solution that minimizes effort and cost. What should you do?

A. Enable automatic backups, and create a read replica of the Cloud SQL instance.

B. Store frequently accessed data in a Memorystore instance.

C. Use Cloud CDN to cache frequently accessed data.

D. Migrate the database to a larger Cloud SQL instance.

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Question #52

You are a database administrator managing sales transaction data by region stored in a BigQuery table. You need to ensure that each sales representative can only see the transactions in their region. What should you do?

A. Create a row-level access policy.

B. Create a data masking rule.

C. Add a policy tag in BigQuery.

D. Grant the appropriate 1AM permissions on the dataset.

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Question #53

Your company has developed a website that allows users to upload and share video files. These files are most frequently accessed and shared when they are initially uploaded. Over time, the files are accessed and shared less frequently, although some old video files may remain very popular. You need to design a storage system that is simple and cost-effective. What should you do?

A. Create a single-region bucket with Autoclass enabled.

B. Create a single-region bucket with custom Object Lifecycle Management policies based on upload date.

C. Create a single-region bucket with Archive as the default storage class.

D. Create a single-region bucket. Configure a Cloud Scheduler job that runs every 24 hours and changes the storage class based on upload date.

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Question #54

You need to create a data pipeline that streams event information from applications in multiple Google Cloud regions into BigQuery for near real-time analysis. The data requires transformation before loading. You want to create the pipeline using a visual interface. What should you do?

A. Push event information to a Pub/Sub topic. Create a BigQuery subscription in Pub/Sub.

B. Push event information to Cloud Storage, and create an external table in BigQuery. Create a BigQuery scheduled job that executes once each day to apply transformations.

C. Push event information to a Pub/Sub topic. Create a Dataflow job using the Dataflow job builder.

D. Push event information to a Pub/Sub topic. Create a Cloud Run function to subscribe to the Pub/Sub topic, apply transformations, and insert the data into BigQuery.

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Correct Answer: C Vote an answer

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Question #55

Your organization uses scheduled queries to perform transformations on data stored in BigQuery. You discover that one of your scheduled queries has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the error details.

B. Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.

C. Set up a log sink using the gcloud CLI to export BigQuery audit logs to BigQuery. Query those logs to identify the error associated with the failed job ID.

D. Navigate to the Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.

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Correct Answer: D Vote an answer

Question #56

Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?

A. Use Cloud Data Fusion pipelines.

B. Use Cloud Composer operators.

C. Use Dataflow pipelines.

D. Use Dataform workflows.

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Correct Answer: D Vote an answer

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Question #57

Your team uses Google Sheets to track budget data that is updated daily. The team wants to compare budget data against actual cost data, which is stored in a BigQuery table. You need to create a solution that calculates the difference between each day's budget and actual costs. You want to ensure that your team has access to daily-updated results in Google Sheets. What should you do?

A. Download the budget data as a CSV file, and upload the CSV file to create a new BigQuery table. Join the actual cost table with the new BigQuery table, and save the results as a CSV file. Open the CSV file in Google Sheets.

B. Create a BigQuery external table by using the Drive URI of the Google sheet, and join the actual cost table with it. Save the joined table as a CSV file and open the file in Google Sheets.

C. Create a BigQuery external table by using the Drive URI of the Google sheet, and join the actual cost table with it. Save the joined table, and open it by using Connected Sheets.

D. Download the budget data as a CSV file and upload the CSV file to a Cloud Storage bucket. Create a new BigQuery table from Cloud Storage, and join the actual cost table with it. Open the joined BigQuery table by using Connected Sheets.

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Correct Answer: C Vote an answer

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Question #58

Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?

A. Create a BigQuery table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.

B. Create a BigQuery table that performs a cross join across all of the regional sales tables. Use the rank() window function to query the new table.

C. Create a BigQuery materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.

D. Create a BigQuery materialized view that performs a cross join across all of the regional sales tables.Use the row_number() window function to query the new materialized view.

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Correct Answer: C Vote an answer

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Question #59

You are building a batch data pipeline to process 100 GB of structured data from multiple sources for daily reporting. You need to transform and standardize the data prior to loading the data to ensure that it is stored in a single dataset. You want to use a low-code solution that can be easily built and managed. What should you do?

A. Use Cloud Data Fusion to ingest the data, perform data cleaning and transformation, and load the data into BigQuery.

B. Use Cloud Storage to store the data. Use Cloud Run functions to perform data cleaning and transformation, and load the data into BigQuery.

C. Use Cloud Data Fusion to ingest the data, perform data cleaning and transformation, and load the data into Cloud SQL for PostgreSQL.

D. Use Cloud Data Fusion to ingest data and load the data into BigQuery. Use Looker Studio to perform data cleaning and transformation.

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Question #60

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 Cloud Monitoring to track key metrics. Create alerting policies in Cloud Monitoring to trigger notifications when metrics exceed thresholds or when errors occur.

B. Use the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.

C. Use Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.

D. 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.

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