免費PDF新版GCP-DE考古題|高通過率的考試材料|一流的GCP-DE：Data Engineer

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Ensuring solution quality	20%-25%	- Data quality management 1. Maintain metadata and lineage 2. Implement data governance 3. Validate and clean data - Security and compliance 1. Implement encryption and compliance controls 2. Protect sensitive data 3. Manage IAM and access control
Managing and optimizing solutions	20%-25%	- Managing resources and costs 1. Optimize storage and compute usage 2. Control operational costs 3. Tune query and pipeline performance - Reliability and scalability 1. Implement disaster recovery strategies 2. Design highly available systems 3. Scale data workloads efficiently
Building and operationalizing data processing systems	28%-33%	- Operationalizing systems 1. Manage logging and alerting 2. Implement fault tolerance and recovery 3. Monitor data pipelines and workloads - Building data processing systems 1. Implement streaming data systems 2. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services 3. Implement batch processing systems
Designing data processing systems	22%-27%	- Designing for data ingestion 1. Design batch and streaming ingestion solutions 2. Select appropriate storage systems 3. Design scalable and reliable ingestion architecture - Designing data pipelines 1. Optimize pipeline performance and cost 2. Design orchestration workflows 3. Build ETL and ELT pipelines

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最新的 Google Cloud Certified GCP-DE 免費考試真題 (Q57-Q62):

問題 #57
You are developing a software application using Google's Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?

A. PCollection
B. Sink API
C. Transform
D. Pipeline

答案：C

解題說明：
In Google Cloud, the Dataflow SDK provides a transform component. It is responsible for the data processing operation. You can use conditional, for loops, and other complex programming structure to create a branching pipeline.
Reference: https://cloud.google.com/dataflow/model/programming-model

問題 #58
You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?

A. Instead of feeding in each feature individually, average their values in batches of 3.
B. Combine highly co-dependent features into one representative feature.
C. Remove the features that have null values for more than 50% of the training records.
D. Eliminate features that are highly correlated to the output labels.

答案：B

問題 #59
You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

A. Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
B. Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP
C. Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
D. Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
E. Create an authorized view in BigQuery to restrict access to tables with sensitive data.

答案：E

問題 #60
You are integrating one of your internal IT applications and Google BigQuery, so users can query BigQuery from the application's interface. You do not want individual users to authenticate to BigQuery and you do not want to give them access to the dataset. You need to securely access BigQuery from your IT application.
What should you do?

A. Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request
B. Use the service account's private key to access the dataset
C. Create a dummy user and grant dataset access to that use
D. Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset
E. Create groups for your users and give those groups access to the dataset
F. Create a service account and grant dataset access to that accoun

答案：F

問題 #61
You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

A. Use the TABLE_DATE_RANGE function
B. Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD
C. Use the WHERE_PARTITIONTIME pseudo column
D. Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD

答案：A

解題說明：
Reference:
https://cloud.google.com/blog/products/gcp/using-bigquery-and-firebase-analytics-to-understandyour-mobile-ap

問題 #62
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