Google GCP-DE New Dumps Ppt | Exam GCP-DE Format

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Designing data processing systems	22%-27%	- Designing for data ingestion 1. Select appropriate storage systems 2. Design scalable and reliable ingestion architecture 3. Design batch and streaming ingestion solutions - Designing data pipelines 1. Build ETL and ELT pipelines 2. Optimize pipeline performance and cost 3. Design orchestration workflows
Ensuring solution quality	20%-25%	- Security and compliance 1. Implement encryption and compliance controls 2. Manage IAM and access control 3. Protect sensitive data - Data quality management 1. Validate and clean data 2. Maintain metadata and lineage 3. Implement data governance
Building and operationalizing data processing systems	28%-33%	- Building data processing systems 1. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services 2. Implement batch processing systems 3. Implement streaming data systems - Operationalizing systems 1. Manage logging and alerting 2. Monitor data pipelines and workloads 3. Implement fault tolerance and recovery
Managing and optimizing solutions	20%-25%	- Reliability and scalability 1. Design highly available systems 2. Scale data workloads efficiently 3. Implement disaster recovery strategies - Managing resources and costs 1. Optimize storage and compute usage 2. Control operational costs 3. Tune query and pipeline performance

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Exam GCP-DE Format, New GCP-DE Test Pdf

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Google Data Engineer Sample Questions (Q57-Q62):

NEW QUESTION # 57
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 # 58
You are implementing several batch jobs that must be executed on a schedule. These jobs have many interdependent steps that must be executed in a specific order. Portions of the jobs involve executing shell scripts, running Hadoop jobs, and running queries in BigQuery. The jobs are expected to run for many minutes up to several hours. If the steps fail, they must be retried a fixed number of times. Which service should you use to manage the execution of these jobs?

A. Cloud Composer
B. Cloud Dataflow
C. Cloud Scheduler
D. Cloud Functions

Answer: C

NEW QUESTION # 59
You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the dat a. Which two actions should you take? (Choose two.)

A. Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
B. Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
C. Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
D. Increase the number of nodes in the Cloud Bigtable cluster
E. Configure your Cloud Dataflow pipeline to use local execution

Answer: A,C

NEW QUESTION # 60
You need to create a data pipeline that copies time-series transaction data so that it can be queried from within BigQuery by your data science team for analysis. Every hour, thousands of transactions are updated with a new status. The size of the intitial dataset is 1.5 PB, and it will grow by 3 TB per day. The data is heavily structured, and your data science team will build machine learning models based on this dat a. You want to maximize performance and usability for your data science team. Which two strategies should you adopt? Choose 2 answers.

A. Use BigQuery'ssupport for external data sources to query.
B. Use BigQuery UPDATE to further reduce the size of the dataset.
C. Denormalize the data as must as possible.
D. Preserve the structure of the data as much as possible.
E. Copy a daily snapshot of transaction data to Cloud Storage and store it as an Avro fil
F. Develop a data pipeline where status updates are appended to BigQuery instead of updated.

Answer: E,F

NEW QUESTION # 61
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. Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.
B. Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.
C. Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
D. Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.

Answer: A

NEW QUESTION # 62
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