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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Ingesting and processing data25%- Transforming data
  • 1. Applying data processing logic
  • 2. Optimizing transformations for performance
  • 3. Managing schema evolution
- Building data pipelines
  • 1. Implementing ingestion mechanisms
  • 2. Developing batch and streaming workflows
  • 3. Handling data quality and consistency
Topic 2: Preparing data for analysis and machine learning13%- 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. Feature engineering and data preparation
  • 2. Supporting model training and serving
Topic 3: Storing and managing data20%- 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. Managing data lifecycle and retention
  • 3. Designing data warehouses and data lakes
Topic 4: Maintaining and automating data workloads18%- Automation and optimization
  • 1. Optimizing resource usage and costs
  • 2. Automating deployment and management
- Operationalizing workloads
  • 1. Orchestrating and scheduling jobs
  • 2. Monitoring and troubleshooting pipelines
  • 3. Ensuring reliability and recoverability
Topic 5: Designing data processing systems24%- Designing data pipelines
  • 1. Designing for data transformation and enrichment
  • 2. Planning for data migration and integration
  • 3. Defining architecture for batch and streaming processing
- Planning data solutions
  • 1. Selecting appropriate storage solutions
  • 2. Designing for reliability, scalability, and efficiency
  • 3. Planning for data security and compliance

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GCP-DE Deutsche, GCP-DE Lernressourcen

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Google Data Engineer GCP-DE Prüfungsfragen mit Lösungen (Q75-Q80):

75. Frage
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.)

Antwort: A,D


76. Frage
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?

Antwort: A


77. Frage
You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

Antwort: D

Begründung:
In Google Cloud dataflow SDK, you can use the ParDo to extract only a customer name of each element in your PCollection.
Reference: https://cloud.google.com/dataflow/model/par-do


78. Frage
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?

Antwort: D


79. Frage
An online retailer has built their current application on Google App Engine. A new initiative at the company mandates that they extend their application to allow their customers to transact directly via the application.
They need to manage their shopping transactions and analyze combined data from multiple datasets using a business intelligence (BI) tool. They want to use only a single database for this purpose. Which Google Cloud database should they choose?

Antwort: C


80. Frage
......

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