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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Operationalizing data and ML pipelines	30%	- Pipeline automation and orchestration 1. Scheduling and monitoring pipelines 2. Cloud Composer workflows - Monitoring and troubleshooting 1. Logging and observability 2. Performance optimization and debugging
Topic 2: Designing data processing systems	20%	- Storage and data modeling 1. Data warehouse design using BigQuery 2. Data lake architecture on Google Cloud Storage - Data pipeline architecture design 1. Scalable data ingestion design 2. Batch vs streaming data processing selection
Topic 3: 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
Topic 4: Maintaining and optimizing data and ML solutions	20%	- Security and governance 1. Data encryption and compliance 2. IAM and access control - Machine learning integration 1. Vertex AI integration for pipelines 2. BigQuery ML usage

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Google Data Engineer Sample Questions (Q66-Q71):

NEW QUESTION # 66
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. Create groups for your users and give those groups access to the dataset
B. Use the service account's private key to access the dataset
C. Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset
D. Create a dummy user and grant dataset access to that use
E. Integrate with a single sign-on (SSO) platform, and pass each user's credentials along with the query request
F. Create a service account and grant dataset access to that accoun

Answer: F

NEW QUESTION # 67
You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

A. An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
B. An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination
C. An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
D. An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination

Answer: A

NEW QUESTION # 68
You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?

A. Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
B. Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
C. Consume the stream of data in Cloud Dataflow using Kafka I
D. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
E. Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
F. If that number falls below 4000, send an alert.
G. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
H. Consume the stream of data in Cloud Dataflow using Kafka I
I. If that number falls below 4000, send an alert.
J. Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
K. Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
L. Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
M. Set a sliding time window of 1 hour every 5 minute

Answer: J

NEW QUESTION # 69
You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are: Decoupling producer from consumer Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely Near real-time SQL query Maintain at least 2 years of historical data, which will be queried with SQ Which pipeline should you use to meet these requirements?

A. Create an application that provides an AP
B. Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
C. Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.
D. Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.
E. Create an application that writes to a Cloud SQL database to store the dat
F. Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.

Answer: A

NEW QUESTION # 70
Which of the following statements is NOT true regarding Bigtable access roles?

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

Answer: C

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 # 71
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