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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 Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.
• B. Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the 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 I
• D. Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.

You need to create a new data pipeline. You want a serverless solution that meets the following requirements:
* Data is streamed from Pub/Sub and is processed in real-time.
* Data is transformed before being stored.
* Data is stored in a location that will allow it to be analyzed with SQL using Looker.
Which Google Cloud services should you recommend for the pipeline?

• A. BigQuery Analytics Hub
• B. Cloud Composer Cloud SQL for MySQL
• C. Dataproc Serverless Bigtable
• D. Dataflow BigQuery

You are designing a BigQuery data warehouse with a team of experienced SQL developers. You need to recommend a cost- effective, fully-managed, serverless solution to build ELT processes with SQL pipelines.
Your solution must include source code control, environment parameterization, and data quality checks. What should you do?

• A. Use Dataform to build, orchestrate, and monitor the pipelines.
• B. Use Dataproc to run MapReduce jobs for distributed data processing.
• C. Use Cloud Composer to orchestrate and run data workflows.
• D. Use Cloud Data Fusion to visually design and manage the pipelines.

Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards.
You need to implement a solution quickly and efficiently. What should you do?

• A. Apply a filter to only show products with a positive profit margin.
• B. Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
• C. Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
• D. Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.

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 materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
• 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 table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.
• 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.