GCP-DE Reliable Mock Test - Latest GCP-DE Test Objectives

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Designing data processing systems	20%	- Storage and data modeling 1. Data lake architecture on Google Cloud Storage 2. Data warehouse design using BigQuery - Data pipeline architecture design 1. Batch vs streaming data processing selection 2. Scalable data ingestion design
Operationalizing data and ML pipelines	30%	- Monitoring and troubleshooting 1. Logging and observability 2. Performance optimization and debugging - Pipeline automation and orchestration 1. Scheduling and monitoring pipelines 2. Cloud Composer workflows
Maintaining and optimizing data and ML solutions	20%	- Machine learning integration 1. Vertex AI integration for pipelines 2. BigQuery ML usage - Security and governance 1. Data encryption and compliance 2. IAM and access control
Building and operationalizing data processing systems	30%	- Data pipeline implementation 1. Dataproc and Spark-based processing 2. Dataflow pipeline development - Data ingestion and transformation 1. Pub/Sub streaming ingestion 2. ETL/ELT workflows

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Latest Google GCP-DE Test Objectives & GCP-DE Practice Exam Pdf

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Google Data Engineer Sample Questions (Q44-Q49):

NEW QUESTION # 44
You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

A. Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
B. Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
C. Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.
D. Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.

Answer: D

NEW QUESTION # 45
You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A. ParDo
B. Data extraction
C. Sink API
D. Source API

Answer: A

Explanation:
In Google Cloud dataflow SDK, you can use the ParDo to extract only a customer name of each element in your PCollection.
Reference: https://cloud.google.com/dataflow/model/par-do

NEW QUESTION # 46
You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A. Add a new column called FullName to the Users tabl
B. Use BigQuery to export the data for the table to a CSV fil
C. Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
D. Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
E. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
F. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.

Answer: E

NEW QUESTION # 47
You need to choose a database for a new project that has the following requirements:
Fully managed
Able to automatically scale up
Transactionally consistent
Able to scale up to 6 TB
Able to be queried using SQL Which database do you choose?

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

Answer: D

NEW QUESTION # 48
You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

A. Process the generated Sentiment Analysis as labels.
B. Build and train a text classification model using TensorFlo
C. Call the Cloud Natural Language API from your applicatio
D. Process the generated Entity Analysis as labels.
E. Deploy the model using a KubernetesEngine cluste
F. Call the model from your application and process the results as labels.
G. Build and train a text classification model using TensorFlo
H. Call the Cloud Natural Language API from your applicatio
I. Deploy the model using Cloud Machine Learning Engin
J. Call the model from your application and process the results as labels.

Answer: D

NEW QUESTION # 49
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