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Google Cloud Associate Data Practitioner Sample Questions (Q65-Q70):
NEW QUESTION # 65
Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on- premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?
Answer: D
Explanation:
Comprehensive and Detailed in Depth Explanation:
Why B is correct:Database Migration Service (DMS) is designed for migrating databases to Cloud SQL with minimal downtime and administrative overhead.
Cloud SQL for MySQL is a fully managed MySQL service, which aligns with the requirement to minimize administrative overhead.
Why other options are incorrect:A: Installing MySQL on Compute Engine requires manual management of the database instance, which increases administrative overhead.
C: BigQuery is not a direct replacement for a relational MySQL database. It's an analytical data warehouse.
D: Spanner is a globally distributed, scalable database, but it requires schema conversion and is not a direct replacement for MySQL, and it is also much more complex than cloud SQL.
NEW QUESTION # 66
Your organization has decided to migrate their existing enterprise data warehouse to BigQuery. The existing data pipeline tools already support connectors to BigQuery. You need to identify a data migration approach that optimizes migration speed. What should you do?
Answer: C
Explanation:
Since your existing data pipeline tools already support connectors to BigQuery, the most efficient approach is touse the existing data pipeline tool's BigQuery connectorto reconfigure the data mapping. This leverages your current tools, reducing migration complexity and setup time, while optimizing migration speed. By reconfiguring the data mapping within the existing pipeline, you can seamlessly direct the data into BigQuery without needing additional services or intermediary steps.
NEW QUESTION # 67
You need to design a data pipeline that ingests data from CSV, Avro, and Parquet files into Cloud Storage. The data includes raw user input. You need to remove all malicious SQL injections before storing the data in BigQuery. Which data manipulation methodology should you choose?
Answer: C
NEW QUESTION # 68
You work for a healthcare company. You have a daily ETL pipeline that extracts patient data from a legacy system, transforms it, and loads it into BigQuery for analysis. The pipeline currently runs manually using a shell script. You want to automate this process and add monitoring to ensure pipeline observability and troubleshooting insights. You want one centralized solution, using open-source tooling, without rewriting the ETL code. What should you do?
Answer: A
Explanation:
Comprehensive and Detailed in Depth Explanation:
Why A is correct:Cloud Composer is a managed Apache Airflow service, which is a popular open-source workflow orchestration tool.
DAGs in Airflow can be used to automate ETL pipelines.
Airflow's web interface and Cloud Monitoring provide comprehensive monitoring capabilities.
It also allows you to run existing shell scripts.
Why other options are incorrect:B: Dataflow requires rewriting the ETL pipeline using its SDK.
C: Dataproc is for big data processing, not orchestration.
D: Cloud Run functions are for stateless applications, not long-running ETL pipelines.
NEW QUESTION # 69
Your organization has a petabyte of application logs stored as Parquet files in Cloud Storage. You need to quickly perform a one-time SQL-based analysis of the files and join them to data that already resides in BigQuery. What should you do?
Answer: D
Explanation:
Creating external tables over the Parquet files in Cloud Storage allows you to perform SQL-based analysis and joins with data already in BigQuery without needing to load the files into BigQuery. This approach is efficient for a one-time analysis as it avoids the time and cost associated with loading large volumes of data into BigQuery. External tables provide seamless integration with Cloud Storage, enabling quick and cost-effective analysis of data stored in Parquet format.
NEW QUESTION # 70
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