Modernizing Data Lakes and Data Warehouses with Google Cloud Syllabus

Overview: This course provides a comprehensive and practical approach to modernizing data lakes and data warehouses using Google Cloud. Learners will explore core concepts, tools, and best practices for implementing scalable data storage solutions in the cloud. The curriculum spans foundational knowledge through hands-on implementation, with a total time commitment of approximately 7 hours. Modules include an introduction to data engineering, building data lakes with Cloud Storage, and leveraging BigQuery for data warehousing. The course concludes with a summary of key insights and learning pathways for continued growth.

Module 1: Introduction to Data Engineering

Estimated time: 1 hour

• Understand the role and responsibilities of a data engineer
• Explore the importance of data engineering in modern businesses
• Examine the benefits of cloud-based data engineering
• Differentiate between data lakes and data warehouses

Module 2: Building a Data Lake

Estimated time: 1 hour

• Define what a data lake is and its core components
• Use Google Cloud Storage as a data lake solution
• Explore use cases for data lakes in various industries
• Evaluate data ingestion and storage best practices

Module 3: Building a Data Warehouse

Estimated time: 5 hours

• Understand the architecture and capabilities of BigQuery
• Implement data warehousing solutions using BigQuery
• Perform querying and analysis on large datasets
• Optimize performance and cost in BigQuery environments

Module 4: Summary

Estimated time: 2 minutes

• Review key concepts from the course
• Reinforce understanding of data lake and warehouse differences
• Highlight the value of cloud-native data storage solutions

Module 5: Final Project

Estimated time: 1 hour

• Design a cloud-based data storage solution combining data lake and warehouse principles
• Justify technology choices using Google Cloud services
• Present a brief overview of implementation strategy and business impact

Prerequisites

• Familiarity with basic data concepts and cloud computing
• Basic understanding of SQL and data querying
• Access to a Google Cloud account for hands-on practice

What You'll Be Able to Do After

• Differentiate between data lakes and data warehouses
• Implement a data lake using Google Cloud Storage
• Build and manage a data warehouse with BigQuery
• Design effective data pipelines in a cloud environment
• Articulate the business value of modern data storage solutions