最新Google GCP-DE考古題 & GCP-DE認證

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Storing and managing data	20%	- Implementing storage solutions 1. Designing data warehouses and data lakes 2. Managing data lifecycle and retention 3. Using data storage services appropriately - Optimizing storage performance and cost 1. Configuring storage for access patterns 2. Implementing cost optimization strategies
Topic 2: Designing data processing systems	24%	- Planning data solutions 1. Designing for reliability, scalability, and efficiency 2. Planning for data security and compliance 3. Selecting appropriate storage solutions - Designing data pipelines 1. Defining architecture for batch and streaming processing 2. Planning for data migration and integration 3. Designing for data transformation and enrichment
Topic 3: Maintaining and automating data workloads	18%	- Operationalizing workloads 1. Monitoring and troubleshooting pipelines 2. Ensuring reliability and recoverability 3. Orchestrating and scheduling jobs - Automation and optimization 1. Automating deployment and management 2. Optimizing resource usage and costs
Topic 4: Preparing data for analysis and machine learning	13%	- Enabling data analysis 1. Optimizing query performance 2. Preparing datasets for querying and reporting 3. Implementing data sharing and governance - Preparing data for ML 1. Feature engineering and data preparation 2. Supporting model training and serving
Topic 5: Ingesting and processing data	25%	- Building data pipelines 1. Developing batch and streaming workflows 2. Implementing ingestion mechanisms 3. Handling data quality and consistency - Transforming data 1. Managing schema evolution 2. Applying data processing logic 3. Optimizing transformations for performance

>> 最新Google GCP-DE考古題 <<

GCP-DE認證，GCP-DE考試大綱

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最新的 Google Cloud Certified GCP-DE 免費考試真題 (Q56-Q61):

問題 #56
You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?

A. Store the data in Google Cloud Datastor
B. Load the data every 30 minutes into a new partitioned table in BigQuery.
C. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
D. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
E. Store the data in a file in a regional Google Cloud Storage bucke
F. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.

答案：B

問題 #57
You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?

A. Cloud Datastore
B. Cloud Spanner
C. Cloud SQL
D. Cloud Bigtable

答案：C

問題 #58
You used Cloud Dataprep to create a recipe on a sample of data in a BigQuery table. You want to reuse this recipe on a daily upload of data with the same schema, after the load job with variable execution time completes. What should you do?

A. Create a cron schedule in Cloud Dataprep.
B. Export the recipe as a Cloud Dataprep template, and create a job in Cloud Scheduler.
C. Export the Cloud Dataprep job as a Cloud Dataflow template, and incorporate it into a Cloud Composer job.
D. Create an App Engine cron job to schedule the execution of the Cloud Dataprep job.

答案：B

問題 #59
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 service account and grant dataset access to that accoun
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 a dummy user and grant dataset access to that use
F. Create groups for your users and give those groups access to the dataset

答案：C

問題 #60
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

A. HTTP
B. HTTPS
C. SOCKS
D. VPN

答案：C

解題說明：
When using Cloud Dataproc clusters, configure your browser to use the SOCKS proxy. The SOCKS proxy routes data intended for the Cloud Dataproc cluster through an SSH tunnel.
Reference: https://cloud.google.com/dataproc/docs/concepts/cluster-web-interfaces#interfaces

問題 #61
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