Course Description

Welcome to "Building Batch Data Pipelines on Google Cloud"! This comprehensive course is designed to equip you with the essential skills and knowledge needed to create efficient and effective data pipelines in the cloud environment. You'll dive deep into the world of data processing paradigms, exploring the nuances of Extract-Load (EL), Extract-Load-Transform (ELT), and Extract-Transform-Load (ETL) methodologies for batch data.

Throughout this course, you'll gain hands-on experience with cutting-edge Google Cloud technologies, including BigQuery, Dataproc, Cloud Data Fusion, and Dataflow. These powerful tools will enable you to transform, process, and analyze data at scale, giving you the expertise to tackle real-world data engineering challenges.

What You'll Learn

• Master the concepts of EL, ELT, and ETL paradigms and learn when to apply each approach
• Develop proficiency in running Hadoop on Dataproc and optimizing Dataproc jobs
• Harness the power of Cloud Storage to enhance data processing efficiency
• Design and implement data processing pipelines using Dataflow
• Gain expertise in managing complex data pipelines with Data Fusion and Cloud Composer
• Apply practical skills through hands-on labs and real-world scenarios

Prerequisites

• Completion of "Google Cloud Big Data and Machine Learning Fundamentals" or equivalent experience
• Basic proficiency in SQL or similar query languages
• Experience with data modeling and ETL activities
• Familiarity with programming, preferably in Python
• Basic understanding of machine learning and statistics concepts

Course Topics

• Introduction to batch data pipelines and their importance in modern data engineering
• In-depth exploration of EL, ELT, and ETL paradigms
• Hadoop implementation on Google Cloud Dataproc
• Optimization techniques for Dataproc jobs
• Leveraging Cloud Storage for enhanced data processing
• Building scalable data processing pipelines with Dataflow
• Managing and orchestrating data pipelines using Cloud Data Fusion
• Workflow management with Cloud Composer
• Best practices for designing efficient and reliable data pipelines
• Hands-on labs and practical exercises using Google Cloud Platform tools

Who This Course Is For

This course is ideal for data engineers, cloud specialists, and IT professionals who want to enhance their skills in building and managing data pipelines on Google Cloud. It's also suitable for developers and data analysts looking to expand their knowledge of cloud-based data processing technologies. Whether you're aiming to advance your career in data engineering or looking to implement efficient data processing solutions for your organization, this course will provide you with the necessary tools and expertise.

Real-World Applications

The skills acquired in this course are directly applicable to real-world scenarios in data engineering and analytics. Learners will be able to:

• Design and implement efficient data pipelines for large-scale data processing in various industries
• Optimize existing data workflows to improve performance and reduce costs
• Leverage Google Cloud technologies to handle big data challenges in their organizations
• Automate data transformation and loading processes for business intelligence and analytics
• Implement best practices in data engineering to ensure data quality and reliability
• Collaborate effectively with data scientists and analysts by providing robust data pipelines
• Contribute to data-driven decision-making processes in their organizations

Syllabus