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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q42-Q47):

NEW QUESTION # 42
Which of the following statements is NOT true regarding Bigtable access roles?

A. To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
B. You can configure access control only at the project level.
C. To give a user access to only one table in a project, you must configure access through your application.
D. Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.

Answer: A

Explanation:
For Cloud Bigtable, you can configure access control at the project level. For example, you can grant the ability to:
Read from, but not write to, any table within the project.
Read from and write to any table within the project, but not manage instances. Read from and write to any table within the project, and manage instances. Reference: https://cloud.google.com/bigtable/docs/access-control

NEW QUESTION # 43
You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A. Create an API using App Engine to receive and send messages to the applications
B. Create a table on Cloud Spanner, and insert and delete rows with the job information
C. Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them
D. Create a table on Cloud SQL, and insert and delete rows with the job information

Answer: C

NEW QUESTION # 44
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. Data extraction
B. Sink API
C. Source API
D. ParDo

Answer: D

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 # 45
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. Build and train a text classification model using TensorFlo
B. Call the model from your application and process the results as labels.
C. Deploy the model using Cloud Machine Learning Engin
D. Build and train a text classification model using TensorFlo
E. Call the Cloud Natural Language API from your applicatio
F. Deploy the model using a KubernetesEngine cluste
G. Process the generated Sentiment Analysis as labels.
H. Process the generated Entity Analysis as labels.
I. Call the Cloud Natural Language API from your applicatio
J. Call the model from your application and process the results as labels.

Answer: H

NEW QUESTION # 46
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 Spanner
B. Cloud Datastore
C. Cloud Bigtable
D. Cloud SQL

Answer: D

NEW QUESTION # 47
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