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- Google GCP-DE Exam Syllabus Topics:
- Section Weight Objectives
- Ensuring solution quality 20%-25% - Data quality management
- Validate and clean data
- Maintain metadata and lineage
- Implement data governance
- Security and compliance
- Implement encryption and compliance controls
- Protect sensitive data
- Manage IAM and access control
- Managing and optimizing solutions 20%-25% - Reliability and scalability
- Scale data workloads efficiently
- Design highly available systems
- Implement disaster recovery strategies
- Managing resources and costs
- Control operational costs
- Optimize storage and compute usage
- Tune query and pipeline performance
- Building and operationalizing data processing systems 28%-33% - Operationalizing systems
- Implement fault tolerance and recovery
- Monitor data pipelines and workloads
- Manage logging and alerting
- Building data processing systems
- Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services
- Implement batch processing systems
- Implement streaming data systems
- Designing data processing systems 22%-27% - Designing for data ingestion
- Select appropriate storage systems
- Design scalable and reliable ingestion architecture
- Design batch and streaming ingestion solutions
- Designing data pipelines
- Design orchestration workflows
- Optimize pipeline performance and cost
- Build ETL and ELT pipelines
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- Google Data Engineer Sample Questions (Q31-Q36):
- NEW QUESTION # 31
- Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
- You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)
- A. Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
- B. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
- C. Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.
- D. Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
- E. Introduce data compression for each file to increase the rate file of file transfer.
- F. Assemble 1,000 files into a tape archive (TAR) fil
- Answer: B,D
- NEW QUESTION # 32
- You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)
- A. Use a larger instance type for your Cloud Dataflow workers
- B. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
- C. Change the zone of your Cloud Dataflow pipeline to run in us-central1
- D. Increase the number of max workers
- E. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
- F. Create a temporary table in Cloud Bigtable that will act as a buffer for new data
- G. Create a temporary table in Cloud Spanner that will act as a buffer for new data
- Answer: A,B
- NEW QUESTION # 33
- Which of the following is NOT true about Dataflow pipelines?
- A. Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources
- B. Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
- C. Dataflow pipelines can consume data from other Google Cloud services
- D. Dataflow pipelines can be programmed in Java
- Answer: B
- Explanation:
- Dataflow pipelines can also run on alternate runtimes like Spark and Flink, as they are built using the Apache Beam SDKs Reference: https://cloud.google.com/dataflow/
- NEW QUESTION # 34
- You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?
- A. Store the data in a file in a regional Google Cloud Storage bucke
- B. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
- C. Load the data every 30 minutes into a new partitioned table in BigQuery.
- D. Use Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.
- E. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
- F. Store the data in Google Cloud Datastor
- Answer: C
- NEW QUESTION # 35
- 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. Configure your Cloud Dataflow pipeline to use local execution
- B. Increase the number of nodes in the Cloud Bigtable cluster
- C. Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
- D. Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
- E. Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
- Answer: D,E
- NEW QUESTION # 36
- .....
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