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GCP-PDE 試験練習問題

Google Professional Data Engineer

GCP-PDE の PDF 練習問題。資料の言語は 英語です。購入はこの試験のみで、自動更新はありません。

試験概要

GCP-PDE は「Google Professional Data Engineer」の認定試験です。試験形式、時間、対応言語は以下をご確認ください。最新の出題範囲や受験条件は公式サイトをご参照ください。

試験コード
GCP-PDE
公式の試験・資格名
Google Professional Data Engineer
試験形式
40–50 single-answer and multiple-select questions (standard exam)
試験時間
120 分
受験可能な言語
英語、日本語

公式試験の対応言語と練習問題ファイルの言語は異なります。試験の版と言語は公式の予約ページでご確認ください。

公式情報： 公式サイト
情報確認日：2026-10-20

対応言語

  • 英語
  • 簡体字中国語
購入前にお試し

最初の 20 問を無料プレビュー

全 349 問

題庫の元の順序で表示します。回答欄を開くと、正解と収録されている解説を確認できます。

問題の言語：英語。問題文・選択肢・正解・解説は元の題庫の言語で表示します。

免責事項：ExamPico の問題はすべてインターネット上の情報を整理したもので、学習参考用として提供しています。

問題 11

Question#11Topic1

You are designing a basket abandonment system for an ecommerce company. The system will send a message to a user based on these rules:
✑ No interaction by the user on the site for 1 hour
Has added more than $30 worth of products to the basket
Question illustration
✑ Has not completed a transaction
You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should you design the pipeline?

  1. A. Use a fixed-time window with a duration of 60 minutes.
  2. B. Use a sliding time window with a duration of 60 minutes.
  3. C. Use a session window with a gap time duration of 60 minutes.
  4. D. Use a global window with a time based trigger with a delay of 60 minutes.
正解を表示

正解

C

問題 12

Question#12Topic1

Your company handles data processing for a number of different clients. Each client prefers to use their own suite of analytics tools, with some allowing direct query access via Google BigQuery. You need to secure the data so that clients cannot see each other's data. You want to ensure appropriate access to the data.
Which three steps should you take? (Choose three.)

  1. A. Load data into different partitions.
  2. B. Load data into a different dataset for each client.
  3. C. Put each client's BigQuery dataset into a different table.
  4. D. Restrict a client's dataset to approved users.
  5. E. Only allow a service account to access the datasets.
  6. F. Use the appropriate identity and access management (IAM) roles for each client's users.
正解を表示

正解

BDF

問題 13

Question#13Topic1

You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.
Which Google database service should you use?

  1. A. Cloud SQL
  2. B. BigQuery
  3. C. Cloud Bigtable
  4. D. Cloud Datastore
正解と解説を表示

正解

D

解説

cloud sql --> incorrect https://cloud.google.com/sql#section-8 --> you will need to manually do scalability Scalability --> Easily scale up as your data grows—add processor cores, RAM and storage, and scale out by adding read replicas to handle increasing read traffic. Read replicas support high availability, can have their own read replicas, and can be located across regions and platforms. big query , big table --> doesn't support ACID Cloud DataStore --> CORRECT ( https://cloud.google.com/datastore/) check features section ACID transactions Ensure the integrity of your data by executing multiple datastore operations in a single transaction with ACID characteristics, so all the grouped operations succeed or all fail. Fully managed Datastore is fully managed, which means Google automatically handles sharding and replication in order to provide you with a highly available and consistent database.

問題 14

Question#14Topic1

You want to use a database of information about tissue samples to classify future tissue samples as either normal or mutated. You are evaluating an unsupervised anomaly detection method for classifying the tissue samples. Which two characteristic support this method? (Choose two.)

  1. A. There are very few occurrences of mutations relative to normal samples.
  2. B. There are roughly equal occurrences of both normal and mutated samples in the database.
  3. C. You expect future mutations to have different features from the mutated samples in the database.
  4. D. You expect future mutations to have similar features to the mutated samples in the database.
  5. E. You already have labels for which samples are mutated and which are normal in the database.
正解と解説を表示

正解

AC

解説

Anomaly detection has two basic assumptions: ->Anomalies only occur very rarely in the data. (a) ->Their features differ from the normal instances significantly. (c) link -> https://towardsdatascience.com/anomaly-detection-for-dummies-15f148e559c1#:~:text=Unsupervised%20Anomaly%20Detection%20for%20Univariate%20%26%20Multivariate%20Data.&text=Anomaly%20detection%20has%20two%20basic,from%20the%20normal%20instances%20significantly.

問題 15

Question#15Topic1

You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?

  1. A. Re-write the application to load accumulated data every 2 minutes.
  2. B. Convert the streaming insert code to batch load for individual messages.
  3. C. Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.
  4. D. Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.
正解を表示

正解

D

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