Associate-Data-Practitionerの無料問題集（74題）、Associate-Data-Practitioner認定試験参考書

Google Associate-Data-Practitioner 問題集

試験コード：Associate-Data-Practitioner

試験名称：Google Cloud Associate Data Practitioner

最近更新時間：2025-01-21

問題と解答：全74問

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質問 1：
You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?
A. Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.
B. Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.
C. Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.
D. Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.
正解：A
解説: (Topexam メンバーにのみ表示されます)

質問 2：
Your organization needs to implement near real-time analytics for thousands of events arriving each second in Pub/Sub. The incoming messages require transformations. You need to configure a pipeline that processes, transforms, and loads the data into BigQuery while minimizing development time. What should you do?
A. Use Cloud Run functions to process the Pub/Sub messages, perform transformations, and write the results to BigQuery.
B. Use a Google-provided Dataflow template to process the Pub/Sub messages, perform transformations, and write the results to BigQuery.
C. Load the data from Pub/Sub into Cloud Storage using a Cloud Storage subscription. Create a Dataproc cluster, use PySpark to perform transformations in Cloud Storage, and write the results to BigQuery.
D. Create a Cloud Data Fusion instance and configure Pub/Sub as a source. Use Data Fusion to process the Pub/Sub messages, perform transformations, and write the results to BigQuery.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 3：
Your organization's business analysts require near real-time access to streaming dat a. However, they are reporting that their dashboard queries are loading slowly. After investigating BigQuery query performance, you discover the slow dashboard queries perform several joins and aggregations.
You need to improve the dashboard loading time and ensure that the dashboard data is as up-to-date as possible. What should you do?
A. Create a scheduled query to calculate and store intermediate results.
B. Disable BiqQuery query result caching.
C. Create materialized views.
D. Modify the schema to use parameterized data types.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 4：
You are responsible for managing Cloud Storage buckets for a research company. Your company has well-defined data tiering and retention rules. You need to optimize storage costs while achieving your data retention needs. What should you do?
A. Configure the buckets to use the Standard storage class and enable Object Versioning.
B. Configure the buckets to use the Autoclass feature.
C. Configure a lifecycle management policy on each bucket to downgrade the storage class and remove objects based on age.
D. Configure the buckets to use the Archive storage class.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 5：
Your organization needs to store historical customer order dat
a. 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 Storage using Standard storage.
B. Store the data in Cloud Storaqe usinq Nearline storaqe.
C. Store the data in Cloud Storaqe usinq Coldline storaqe.
D. Store the data in Cloud Storage using Archive storage.
正解：B
解説: (Topexam メンバーにのみ表示されます)

質問 6：
Your organization stores highly personal data in BigQuery and needs to comply with strict data privacy regulations. You need to ensure that sensitive data values are rendered unreadable whenever an employee leaves the organization. What should you do?
A. Use dynamic data masking and revoke viewer permissions when employees leave the organization.
B. Use column-level access controls with policy tags and revoke viewer permissions when employees leave the organization.
C. Use customer-managed encryption keys (CMEK) and delete keys when employees leave the organization.
D. Use AEAD functions and delete keys when employees leave the organization.
正解：C
解説: (Topexam メンバーにのみ表示されます)

質問 7：
You have millions of customer feedback records stored in BigQuery. You want to summarize the data by using the large language model (LLM) Gemini. You need to plan and execute this analysis using the most efficient approach. What should you do?
A. Export the raw BigQuery data to a CSV file, upload it to Cloud Storage, and use the Gemini API to summarize the data.
B. Create a BigQuery Cloud resource connection to a remote model in Vertex Al, and use Gemini to summarize the data.
C. Use a BigQuery ML model to pre-process the text data, export the results to Cloud Storage, and use the Gemini API to summarize the pre- processed data.
D. Query the BigQuery table from within a Python notebook, use the Gemini API to summarize the data within the notebook, and store the summaries in BigQuery.
正解：B
解説: (Topexam メンバーにのみ表示されます)

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Google Cloud Associate Data Practitioner 認定 Associate-Data-Practitioner 試験問題:

1. You work for a financial services company that handles highly sensitive dat a. Due to regulatory requirements, your company is required to have complete and manual control of data encryption. Which type of keys should you recommend to use for data storage?

A) Use customer-managed encryption keys (CMEK).
B) Use customer-supplied encryption keys (CSEK).
C) Use a dedicated third-party key management system (KMS) chosen by the company.
D) Use Google-managed encryption keys (GMEK).

2. You are working with a large dataset of customer reviews stored in Cloud Storage. The dataset contains several inconsistencies, such as missing values, incorrect data types, and duplicate entries. You need to clean the data to ensure that it is accurate and consistent before using it for analysis. What should you do?

A) Use BigQuery to batch load the data into BigQuery. Use SQL for cleaning and analysis.
B) Use Storage Transfer Service to move the data to a different Cloud Storage bucket. Use event triggers to invoke Cloud Run functions to load the data into BigQuery. Use SQL for analysis.
C) Use the PythonOperator in Cloud Composer to clean the data and load it into BigQuery. Use SQL for analysis.
D) Use Cloud Run functions to clean the data and load it into BigQuery. Use SQL for analysis.

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

4. Another team in your organization is requesting access to a BigQuery dataset. You need to share the dataset with the team while minimizing the risk of unauthorized copying of dat a. You also want to create a reusable framework in case you need to share this data with other teams in the future. What should you do?

A) Create a private exchange using Analytics Hub with data egress restriction, and grant access to the team members.
B) Export the dataset to a Cloud Storage bucket in the team's Google Cloud project that is only accessible by the team.
C) Create authorized views in the team's Google Cloud project that is only accessible by the team.
D) Enable domain restricted sharing on the project. Grant the team members the BigQuery Data Viewer IAM role on the dataset.

5. 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?

A) ETL
B) EL
C) ETLT
D) ELT

質問と回答：

質問 # 1
正解： B

質問 # 2
正解： A

質問 # 3
正解： D

質問 # 4
正解： A

質問 # 5
正解： A