Course Description

Course Overview

The Data Integration with Cloud Data Fusion course is designed to provide individuals with the knowledge and skills necessary to effectively integrate and transform data using Cloud Data Fusion, a fully managed data integration service on Google Cloud Platform (GCP). This course covers the fundamentals of data integration, data pipelines, and data transformation using Cloud Data Fusion’s visual interface.

Prerequisites

To enroll in the Data Integration with Cloud Data Fusion course, participants should have a basic understanding of data integration concepts and familiarity with GCP fundamentals. Prior experience with data ingestion, transformation, and ETL (Extract, Transform, Load) processes will be beneficial. Participants should also have access to a GCP project or demo environment to practice the concepts covered in the course.

Methodology

The Data Integration with Cloud Data Fusion course follows a blended learning approach, combining theoretical instruction, demonstrations, and hands-on labs. Participants will engage in instructor-led sessions where data integration concepts and best practices are explained. They will also have access to Cloud Data Fusion’s visual interface to gain practical experience in building data integration pipelines. The course encourages active participation, discussions, and collaborative problem-solving to reinforce learning.

Course Outline

Introduction to Data Integration and Cloud Data Fusion

Overview of data integration concepts and challenges

Understanding Cloud Data Fusion’s features and capabilities

Exploring the Cloud Data Fusion interface and components

Data Pipeline Development in Cloud Data Fusion

Creating and configuring data pipelines in Cloud Data Fusion

Utilizing data sources, sinks, and transformations

Configuring pipeline schedules and triggers

Data Transformation and Wrangling in Cloud Data Fusion

Performing data transformation operations using Wrangler

Cleaning, parsing, and filtering data

Joining, aggregating, and enriching data

Data Integration Best Practices and Optimization

Applying best practices for efficient data integration

Optimizing data pipelines for performance and scalability

Monitoring and troubleshooting data integration processes

Real-time and Streaming Data Integration

Working with real-time and streaming data sources

Configuring streaming data pipelines in Cloud Data Fusion

Transforming and processing streaming data in real-time

Data Integration with External Systems

Integrating Cloud Data Fusion with other GCP services

Utilizing external systems for data ingestion and delivery

Implementing data integration workflows with Cloud Composer

Outcome

By the end of the Data Integration with Cloud Data Fusion course, participants will have:

• Developed a comprehensive understanding of data integration concepts and best practices
• Acquired practical knowledge in building data integration pipelines using Cloud Data Fusion
• Gained expertise in data transformation and wrangling using Cloud Data Fusion’s visual interface
• Learned techniques for optimizing data integration processes for performance and scalability
• Gained hands-on experience through practical labs and exercises
• Prepared to integrate and transform data effectively using Cloud Data Fusion in the GCP environment

Labs

The Data Integration with Cloud Data Fusion course includes hands-on labs that provide participants with practical experience in building data integration pipelines and performing data transformation using Cloud Data Fusion. Some examples of lab exercises include:

• Creating a data pipeline in Cloud Data Fusion using different data sources and sinks
• Configuring transformations and filters in Cloud Data Fusion’s visual interface
• Implementing data cleansing and enrichment operations using Wrangler
• Optimizing data integration pipelines for performance and scalability
• Configuring real-time and streaming data integration pipelines
• Integrating Cloud Data Fusion with other GCP services and external systems

These labs enable participants to apply the concepts learned in the course and gain hands-on experience in data integration and transformation using Cloud Data Fusion, allowing them to develop practical skills in building efficient and scalable data integration pipelines in the GCP environment.