Associate-Data-Practitioner無料問題集「Google Cloud Associate Data Practitioner」

質問 1

Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

（A）Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.

（B）Use the gcloud storage cp command to copy all files from on-premises to Cloud Storage using the --no- clobber option.

（C）Use the gcloud storage cp command to copy all files from on-premises to Cloud Storage using the -- daisy-chain option.

（D）Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 2

You have a BigQuery dataset containing sales data. This data is actively queried for the first 6 months. After that, the data is not queried but needs to be retained for 3 years for compliance reasons. You need to implement a data management strategy that meets access and compliance requirements, while keeping cost and administrative overhead to a minimum. What should you do?

（A）Set up a scheduled query to export the data to Cloud Storage after 6 months. Write a stored procedure to delete the data from BigQuery after 3 years.

（B）Store all data in a single BigQuery table without partitioning or lifecycle policies.

（C）Partition a BigQuery table by month. After 6 months, export the data to Coldline storage. Implement a lifecycle policy to delete the data from Cloud Storage after 3 years.

（D）Use BigQuery long-term storage for the entire dataset. Set up a Cloud Run function to delete the data from BigQuery after 3 years.

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 3

Your company's customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files' metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?

（A）Create a native table.

（B）Create an external table.

（C）Create a temporary table.

（D）Create an object table.

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 4

You are designing a pipeline to process data files that arrive in Cloud Storage by 3:00 am each day. Data processing is performed in stages, where the output of one stage becomes the input of the next. Each stage takes a long time to run. Occasionally a stage fails, and you have to address the problem. You need to ensure that the final output is generated as quickly as possible. What should you do?

（A）Design the workflow as a Cloud Workflow instance. Code the workflow to jump to a given stage based on an input parameter. Rerun the workflow after correcting any stage output data errors.

（B）Design the pipeline as a set of PTransforms in Dataflow. Restart the pipeline after correcting any stage output data errors.

（C）Design the processing as a directed acyclic graph (DAG) in Cloud Composer. Clear the state of the failed task after correcting any stage output data errors.

（D）Design a Spark program that runs under Dataproc. Code the program to wait for user input when an error is detected. Rerun the last action after correcting any stage output data errors.

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 5

Your organization needs to store historical customer order data. The data will only be accessed once a month for analysis and must be readily available within a few seconds when it is accessed. You need to choose a storage class that minimizes storage costs while ensuring that the data can be retrieved quickly. What should you do?

（A）Store the data in Cloud Storaqe usinq Coldline storaqe.

（B）Store the data in Cloud Storaqe usinq Nearline storaqe.

（C）Store the data in Cloud Storage using Archive storage.

（D）Store the data in Cloud Storage using Standard storage.

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 6

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）Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.

（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）Apply a filter to only show products with a positive profit margin.

正解：C 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 7

Your organization plans to move their on-premises environment to Google Cloud. Your organization's network bandwidth is less than 1 Gbps. You need to move over 500 ## of data to Cloud Storage securely, and only have a few days to move the data. What should you do?

（A）Connect to Google Cloud using Dedicated Interconnect. Use the gcloud storage command to move the data to Cloud Storage.

（B）Request multiple Transfer Appliances, copy the data to the appliances, and ship the appliances back to Google Cloud to upload the data to Cloud Storage.

（C）Connect to Google Cloud using VPN. Use the gcloud storage command to move the data to Cloud Storage.

（D）Connect to Google Cloud using VPN. Use Storage Transfer Service to move the data to Cloud Storage.

正解：B 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 8

Your organization consists of two hundred employees on five different teams. The leadership team is concerned that any employee can move or delete all Looker dashboards saved in the Shared folder. You need to create an easy-to-manage solution that allows the five different teams in your organization to view content in the Shared folder, but only be able to move or delete their team-specific dashboard. What should you do?

（A）1. Create Looker groups representing each of the five different teams, and add users to their corresponding group. 2. Create five subfolders inside the Shared folder. Grant each group the View access level to their corresponding subfolder.

（B）1. Move all team-specific content into the dashboard owner s personal folder. 2. Change the access level of the Shared folder to View for the All Users group. 3. Instruct each user to create content for their team in the user's personal folder.

（C）1. Change the access level of the Shared folder to View for the All Users group. 2. Create five subfolders inside the Shared folder. Grant each team member the Manage Access, Edit access level to their corresponding subfolder.

（D）1. Change the access level of the Shared folder to View for the All Users group. 2. Create Looker groups representing each of the five different teams, and add users to their corresponding group. 3.
Create five subfolders inside the Shared folder. Grant each group the Manage Access, Edit access level to their corresponding subfolder.

正解：D 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 9

You need to create a data pipeline for a new application. Your application will stream data that needs to be enriched and cleaned. Eventually, the data will be used to train machine learning models. You need to determine the appropriate data manipulation methodology and which Google Cloud services to use in this pipeline. What should you choose?

（A）ETL; Dataflow -> BigQuery

（B）ELT; Cloud Storage -> Bigtable

（C）ELT; Cloud SQL -> Analytics Hub

（D）ETL; Cloud Data Fusion -> Cloud Storage

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

質問 10

You work for a healthcare company that has a large on-premises data system containing patient records with personally identifiable information (PII) such as names, addresses, and medical diagnoses. You need a standardized managed solution that de-identifies PII across all your data feeds prior to ingestion to Google Cloud. What should you do?

（A）Use Cloud Data Fusion to transform the data. Store the cleaned data in BigQuery.

（B）Use Apache Beam to read the data and perform the necessary cleaning and transformation operations.Store the cleaned data in BigQuery.

（C）Load the data into BigQuery, and inspect the data by using SQL queries. Use Dataflow to transform the data and remove any errors.

（D）Use Cloud Run functions to create a serverless data cleaning pipeline. Store the cleaned data in BigQuery.

正解：A 解答を投票する

解説: (JPNTest メンバーにのみ表示されます)

Associate-Data-Practitioner 無料問題集「Google Cloud Associate Data Practitioner」

弊社を連絡する

関連リンク

トップ試験