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Professional-Data-Engineer試験の準備方法｜効率的なProfessional-Data-Engineer対応内容試験｜一番優秀なGoogle Certified Professional Data Engineer Exam的中問題集
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Google Certified Professional Data Engineer 試験は、Google Cloud Platform上でデータ処理システムを設計および構築する知識を持つ個人を対象として、Googleから提供されている認定試験です。この試験は、Google Cloud Platform上のデータ処理システム、機械学習、データ分析ツールに関する候補者の知識を試験するように作られています。
Google Professional-Data-Engineer試験は、Google Cloudテクノロジーを使用したデータエンジニアリングにおける個人のスキルと知識を厳しくテストするものです。熟練したデータエンジニアリング専門家の需要が増えるにつれて、この認定は、業界で自分の地位を確立したい人にとって、多くの利益のある求人機会を提供することができます。認定プロセスには、実務経験、幅広い準備、そして今日の急速に進化するテクノロジー生態系で高く評価されるスキルを習得するための献身が必要です。
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Google Professional-Data-Engineer的中問題集 & Professional-Data-Engineer問題サンプル
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Google Certified Professional Data Engineer Exam 認定 Professional-Data-Engineer 試験問題 (Q223-Q228):
質問 # 223
You are designing a data mesh on Google Cloud by using Dataplex to manage data in BigQuery and Cloud Storage. You want to simplify data asset permissions. You are creating a customer virtual lake with two user groups:
* Data engineers, which require lull data lake access
* Analytic users, which require access to curated data
You need to assign access rights to these two groups. What should you do?
- A. 1. Grant the dataplex.dataReader role to the data engineer group on the customer data lake.
2. Grant the dataplex.dataOwner to the analytic user group on the customer curated zone. - B. 1. Grant the bigquery.dataViewer role on BigQuery datasets and the storage.objectviewer role on Cloud Storage buckets to data engineers.
2. Grant the bigquery.dataOwner role on BigQuery datasets and the storage.objectEditor role on Cloud Storage buckets to analytic users. - C. 1. Grant the bigquery.dataownex role on BigQuery datasets and the storage.objectcreator role on Cloud Storage buckets to data engineers.
2. Grant the bigquery.dataViewer role on BigQuery datasets and the storage.objectViewer role on Cloud Storage buckets to analytic users. - D. 1. Grant the dataplex.dataOwner role to the data engineer group on the customer data lake.
2. Grant the dataplex.dataReader role to the analytic user group on the customer curated zone.
正解：D
解説：
When designing a data mesh on Google Cloud using Dataplex to manage data in BigQuery and Cloud Storage, it is essential to simplify data asset permissions while ensuring that each user group has the appropriate access levels. Here's why option A is the best choice:
Data Engineer Group:
Data engineers require full access to the data lake to manage and operate data assets comprehensively. Granting the dataplex.dataOwner role to the data engineer group on the customer data lake ensures they have the necessary permissions to create, modify, and delete data assets within the lake.
Analytic User Group:
Analytic users need access to curated data but do not require full control over all data assets. Granting the dataplex.dataReader role to the analytic user group on the customer curated zone provides read-only access to the curated data, enabling them to analyze the data without the ability to modify or delete it.
Steps to Implement:
Grant Data Engineer Permissions:
Assign the dataplex.dataOwner role to the data engineer group on the customer data lake to ensure full access and management capabilities.
Grant Analytic User Permissions:
Assign the dataplex.dataReader role to the analytic user group on the customer curated zone to provide read-only access to curated data.
Reference:
Dataplex IAM Roles and Permissions
Managing Access in Dataplex
質問 # 224
You are on the data governance team and are implementing security requirements to deploy resources. You need to ensure that resources are limited to only the europe-west 3 region You want to follow Google-recommended practices What should you do?
- A. Set the constraints/gcp. resourceLocations organization policy constraint to in: europe-west3-locations.
- B. Deploy resources with Terraform and implement a variable validation rule to ensure that the region is set to the europe-west3 region for all resources.
- C. Create a Cloud Function to monitor all resources created and automatically destroy the ones created outside the europe-west3 region.
- D. Set the constraints/gcp. resourceLocations organization policy constraint to in:eu-locations.
正解：A
解説：
To ensure that resources are limited to only the europe-west3 region, you should set the organization policy constraint constraints/gcp.resourceLocations to in:europe-west3-locations. This policy restricts the deployment of resources to the specified locations, which in this case is the europe-west3 region. By setting this policy, you enforce location compliance across your Google Cloud resources, aligning with the best practices for data governance and regulatory compliance.
Reference:
Professional Data Engineer Certification Exam Guide | Learn - Google Cloud1.
Preparing for Google Cloud Certification: Cloud Data Engineer2.
Professional Data Engineer Certification | Learn | Google Cloud3.
3: Professional Data Engineer Certification | Learn | Google Cloud 2: Preparing for Google Cloud Certification: Cloud Data Engineer 1: Professional Data Engineer Certification Exam Guide | Learn - Google Cloud
質問 # 225
You work for an airline and you need to store weather data in a BigQuery table Weather data will be used as input to a machine learning model. The model only uses the last 30 days of weather data. You want to avoid storing unnecessary data and minimize costs. What should you do?
- A. Create a BigQuery table where each record has an ingestion timestamp Run a scheduled query to delete all the rows with an ingestion timestamp older than 30 days.
- B. Create a BigQuery table partitioned by ingestion time Set up partition expiration to 30 days.
- C. Create a BigQuery table partitioned by datetime value of the weather date Set up partition expiration to
30 days. - D. Create a BigQuery table with a datetime column for the day the weather data refers to. Run a scheduled query to delete rows with a datetime value older than 30 days.
正解：B
解説：
Partitioning a table by ingestion time means that the data is divided into partitions based on the time when the data was loaded into the table. This allows you to delete or archive old data by setting a partition expiration policy. You can specify the number of days to keep the data in each partition, and BigQuery automatically deletes the data when it expires. This way, you can avoid storing unnecessary data and minimize costs.
質問 # 226
Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?
- A. Get the identity and access management IIAM) policy of each table
- B. Use the Google Cloud Billing API to see what account the warehouse is being billed to.
- C. Use Google Stackdriver Audit Logs to review data access.
- D. Use Stackdriver Monitoring to see the usage of BigQuery query slots.
正解：D
質問 # 227
A data scientist has created a BigQuery ML model and asks you to create an ML pipeline to serve predictions. You have a REST API application with the requirement to serve predictions for an individual user ID with latency under 100 milliseconds. You use the following query to generate predictions: SELECT predicted_label, user_id FROM ML.PREDICT (MODEL `dataset.model', table . How should you create the ML pipeline?
user_features)
- A. Add a WHERE clause to the query, and grant the BigQuery Data Viewer role to the application service account.
- B. Create a Cloud Dataflow pipeline using BigQueryIO to read predictions for all users from the query.
Write the results to Cloud Bigtable using BigtableIO. Grant the Bigtable Reader role to the application service account so that the application can read predictions for individual users from Cloud Bigtable. - C. Create an Authorized View with the provided query. Share the dataset that contains the view with the application service account.
- D. Create a Cloud Dataflow pipeline using BigQueryIO to read results from the query. Grant the Dataflow Worker role to the application service account.
正解：B
質問 # 228
......
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