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100% Pass Quiz Google - Efficient Associate-Data-Practitioner - New Google Cloud Associate Data Practitioner Test Fee

100% Pass Quiz Google - Efficient Associate-Data-Practitioner - New Google Cloud Associate Data Practitioner Test Fee

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Google Cloud Associate Data Practitioner Sample Questions (Q44-Q49):

NEW QUESTION # 44
You are a data analyst at your organization. You have been given a BigQuery dataset that includes customer information. The dataset contains inconsistencies and errors, such as missing values, duplicates, and formatting issues. You need to effectively and quickly clean the dat a. What should you do?

  • A. Use Cloud Data Fusion to create a data pipeline to read the data from BigQuery, perform data quality transformations, and write the clean data back to BigQuery.
  • B. Export the data from BigQuery to CSV files. Resolve the errors using a spreadsheet editor, and re-import the cleaned data into BigQuery.
  • C. Develop a Dataflow pipeline to read the data from BigQuery, perform data quality rules and transformations, and write the cleaned data back to BigQuery.
  • D. Use BigQuery's built-in functions to perform data quality transformations.

Answer: D

Explanation:
Using BigQuery's built-in functions is the most effective and efficient way to clean the dataset directly within BigQuery. BigQuery provides powerful SQL capabilities to handle missing values, remove duplicates, and resolve formatting issues without needing to export data or create complex pipelines. This approach minimizes overhead and leverages the scalability of BigQuery for large datasets, making it an ideal solution for quickly addressing data quality issues.


NEW QUESTION # 45
You manage a Cloud Storage bucket that stores temporary files created during data processing. These temporary files are only needed for seven days, after which they are no longer needed. To reduce storage costs and keep your bucket organized, you want to automatically delete these files once they are older than seven days. What should you do?

  • A. Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
  • B. Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.
  • C. Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
  • D. Create a Cloud Run function that runs daily and deletes files older than seven days.

Answer: C

Explanation:
Configuring a Cloud Storage lifecycle rule to automatically delete objects older than seven days is the best solution because:
Built-in feature: Cloud Storage lifecycle rules are specifically designed to manage object lifecycles, such as automatically deleting or transitioning objects based on age.
No additional setup: It requires no external services or custom code, reducing complexity and maintenance.
Cost-effective: It directly achieves the goal of deleting files after seven days without incurring additional compute costs.


NEW QUESTION # 46
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. Configure a Cloud Scheduler job that runs every 24 hours and changes the storage class based on upload date.
  • 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 with Autoclass enabled.

Answer: B

Explanation:
Creating a single-region bucket with custom Object Lifecycle Management policies based on upload date is the most appropriate solution. This approach allows you to automatically transition objects to less expensive storage classes as their access frequency decreases over time. For example, frequently accessed files can remain in the Standard storage class initially, then transition to Nearline, Coldline, or Archive storage as their popularity wanes. This strategy ensures a cost-effective and efficient storage system while maintaining simplicity by automating the lifecycle management of video files.


NEW QUESTION # 47
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. Create a batch pipeline in Dataflow by using the Cloud Storage CSV file to BigQuery batch template.
  • B. Create a batch pipeline in Cloud Data Fusion by using a Cloud Storage source and a BigQuery sink.
  • C. Load the CSV file as a table in BigQuery, and use scheduled queries to run SQL transformation scripts.
  • D. Load the CSV file as a table in BigQuery. Create a batch pipeline in Cloud Data Fusion by using a BigQuery source and sink.

Answer: B

Explanation:
Using Cloud Data Fusion to create a batch pipeline with a Cloud Storage source and a BigQuery sink is the best solution because:
Scalability: Cloud Data Fusion is a scalable, fully managed data integration service.
Data transformation: It provides a visual interface to design pipelines, enabling quick transformation of data.
Data quality insights: Cloud Data Fusion includes built-in tools for monitoring and addressing data quality issues during the pipeline creation and execution process.


NEW QUESTION # 48
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. Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.
  • D. Define a new measure that calculates the profit margin by using the existing revenue and cost fields.

Answer: D

Explanation:
Defining a new measure in LookML to calculate the profit margin using the existing revenue and cost fields is the most efficient and straightforward solution. This approach allows you to dynamically compute the profit margin directly within your Looker Explores and dashboards without needing to pre-calculate or create additional tables. The measure can be defined using LookML syntax, such as:
measure: profit_margin {
type: number
sql: (revenue - cost) / revenue ;;
value_format: "0.0%"
}
This method is quick to implement and integrates seamlessly into your existing Looker model, enabling accurate visualization of profit margins across your products.


NEW QUESTION # 49
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