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Google Cloud Professional Data Engineer - GCP PDE Mock Tests
Rating: 5.0 out of 5(2 ratings)
16 students

Google Cloud Professional Data Engineer - GCP PDE Mock Tests

Master Google Cloud Data Engineering: Data Processing, Storage Solutions, and Automated Workflows
Last updated 11/2024
English

What you'll learn

  • Design and Optimize Data Processing Systems
  • Implement Data Ingestion and Transformation Pipelines
  • Apply Data Storage Solutions Effectively
  • Automate and Monitor Data Workloads

Included in This Course

120 questions
  • Mock Test #160 questions
  • Mock Test #260 questions

Description

This course is designed to equip you with essential skills in data engineering on Google Cloud Platform (GCP). Through hands-on labs and real-world scenarios, you’ll learn how to design, implement, and automate data pipelines that are efficient, scalable, and reliable. We’ll cover core GCP services for data engineering, including Cloud Pub/Sub for streaming data ingestion, Cloud Dataflow for data transformation, BigQuery for advanced analytics, and Cloud Composer for orchestration and workflow automation.


You’ll start by mastering data ingestion techniques for both batch and streaming data, then move on to data transformation and storage optimization using GCP’s best practices. Additionally, you’ll learn how to monitor and automate your data workflows, ensuring data quality, integrity, and operational efficiency. By the end of the course, you’ll be able to design end-to-end data pipelines tailored to specific business needs, prepare data for analytics and machine learning, and manage these processes with minimal maintenance.


This course is ideal for data professionals, cloud engineers, and IT specialists looking to deepen their expertise in data engineering and automation on Google Cloud. Whether you're preparing for the Google Professional Data Engineer Certification or aiming to build advanced data engineering skills, this course provides the practical experience needed to succeed.

Who this course is for:

  • Data Professionals
  • Data Engineers
  • Cloud Practitioners
  • Data Analysts
  • BI Professionals
  • Solution Architects