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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q48-Q53):

NEW QUESTION # 48
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, you must configure access through your application.
B. You can configure access control only at the project level.
C. Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.
D. To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.

Answer: D

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 # 49
You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
B. Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
C. Deploy the Cloud SQL Proxy on the Cloud Dataproc master
D. Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter

Answer: B

NEW QUESTION # 50
You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

A. Workflow Templates on Cloud Dataproc
B. Cloud Scheduler
C. Cloud Composer
D. cron

Answer: A

NEW QUESTION # 51
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 WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD
B. Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD
C. Use the TABLE_DATE_RANGE function
D. Use the WHERE_PARTITIONTIME pseudo column

Answer: C

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

NEW QUESTION # 52
You want to migrate an on-premises Hadoop system to Cloud Dataproc. Hive is the primary tool in use, and the data format is Optimized Row Columnar (ORC). All ORC files have been successfully copied to a Cloud Storage bucket. You need to replicate some data to the cluster's local Hadoop Distributed File System (HDFS) to maximize performance. What are two ways to start using Hive in Cloud Dataproc? (Choose two.)

A. Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to the master node of the Dataproc cluste
B. Replicate external Hive tables to the native ones.
C. Mount the Hive tables locally.
D. Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to HDF
E. Mount the Hive tables locally.
F. Leverage BigQuery connector for Hadoop to mount the BigQuery tables as external Hive table
G. Leverage Cloud Storage connector for Hadoop to mount the ORC files as external Hive table
H. Run the gsutil utility to transfer all ORC files from the Cloud Storage bucket to any node of the Dataproc cluste
I. Then run the Hadoop utility to copy them do HDF
J. Mount the Hive tables from HDFS.
K. Replicate external Hive tables to the native ones.
L. Load the ORC files into BigQuer

Answer: E,H

NEW QUESTION # 53
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