Quiz Google - Accurate GCP-DE - Test Data Engineer Prep

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| Section | Weight | Objectives |
|---|
| Building and operationalizing data processing systems | 28%-33% | - Building data processing systems
- 1. Implement streaming data systems
- 2. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
- 3. Implement batch processing systems
- Operationalizing systems
- 1. Manage logging and alerting
- 2. Monitor data pipelines and workloads
- 3. Implement fault tolerance and recovery
|
| Ensuring solution quality | 20%-25% | - Security and compliance
- 1. Protect sensitive data
- 2. Implement encryption and compliance controls
- 3. Manage IAM and access control
- Data quality management
- 1. Validate and clean data
- 2. Maintain metadata and lineage
- 3. Implement data governance
|
| Managing and optimizing solutions | 20%-25% | - Reliability and scalability
- 1. Implement disaster recovery strategies
- 2. Scale data workloads efficiently
- 3. Design highly available systems
- Managing resources and costs
- 1. Tune query and pipeline performance
- 2. Control operational costs
- 3. Optimize storage and compute usage
|
| Designing data processing systems | 22%-27% | - Designing data pipelines
- 1. Build ETL and ELT pipelines
- 2. Design orchestration workflows
- 3. Optimize pipeline performance and cost
- Designing for data ingestion
- 1. Design batch and streaming ingestion solutions
- 2. Select appropriate storage systems
- 3. Design scalable and reliable ingestion architecture
|
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Google Data Engineer Sample Questions (Q54-Q59):
NEW QUESTION # 54
What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?
- A. Windows
- B. Sessions
- C. Triggers
- D. OutputCriteria
Answer: C
Explanation:
Triggers control when the elements for a specific key and window are output. As elements arrive, they are put into one or more windows by a Window transform and its associated WindowFn, and then passed to the associated Trigger to determine if the Windows contents should be output.
Reference:
https://cloud.google.com/dataflow/java-sdk/JavaDoc/com/google/cloud/dataflow/sdk/transforms/windowing/Tri
NEW QUESTION # 55
MJTelco is building a custom interface to share dat
a. They have these requirements:
They need to do aggregations over their petabyte-scale datasets.
They need to scan specific time range rows with a very fast response time (milliseconds). Which combination of Google Cloud Platform products should you recommend?
- A. BigQuery and Cloud Storage
- B. Cloud Bigtable and Cloud SQL
- C. BigQuery and Cloud Bigtable
- D. Cloud Datastore and Cloud Bigtable
Answer: C
NEW QUESTION # 56
You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?
- A. Create an authorized view in BigQuery to restrict access to tables with sensitive data.
- B. Use the tagging and confidence levels to either pass or quarantine the data in a bucket for review.
- C. Build a Cloud Function that reads the topics and makes a call to the Cloud Data Loss Prevention AP
- D. Install a third-party data validation tool on Compute Engine virtual machines to check the incoming data for sensitive information.
- E. Use Stackdriver logging to analyze the data passed through the total pipeline to identify transactions that may contain sensitive information.
Answer: A
NEW QUESTION # 57
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 # 58
You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?
- A. Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances.Store data in HDF
- B. Use a standard persistent disk and 50% preemptible worker
- C. Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instance
- D. Deploy a Cloud Dataproc cluste
- E. Change references in scripts from hdfs:// to gs://
- F. Install the Cloud Storage connector, and store the data in Cloud Storag
- G. Deploy a Cloud Dataproc cluste
- H. Use an SSD persistent disk and 50% preemptible worker
- I. Change references in scripts from hdfs:// to gs://
- J. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
- K. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
Answer: D
NEW QUESTION # 59
......
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