Module 1: Data Warehouse Fundamentals (Week 1)

• Understand the core concepts of data warehousing and its benefits for business intelligence.

• Explore different data warehouse architectures like Kimball and Inmon models.

• Learn the key components of a DWH, including data staging area, data mart, and data warehouse.

Module 2: PostgreSQL for Data Warehousing (Week 1)

• Delve into the strengths of PostgreSQL for building scalable and reliable DWHs.

• Master the advantages of open-source databases for data warehousing projects.

• Understand how PostgreSQL supports data types, data integrity, and complex queries.

Module 3: Data Warehouse Infrastructure (Week 2)

• Explore the infrastructure considerations for building a DWH solution.

• Understand the role of data extraction, transformation, and loading (ETL) processes.

• Learn about data warehouse servers, storage options, and data security best practices.

Module 4: Data Modeling for DWHs (Week 2)

• Master data modeling techniques for efficient data organization in a DWH.

• Understand the importance of dimensional modeling and its benefits.

• Apply dimensional modeling concepts like star schemas and snowflake schemas.

Module 5: Dimensional Modeling: Facts & Dimensions (Week 3)

• Delve into the details of facts and dimensions in a DWH schema.

• Learn how to identify facts (measures) and dimensions (attributes) in your data.

• Design fact tables and dimension tables for optimal data retrieval and analysis.

Module 6: Implementing a Complete Data Warehouse (Weeks 3)

• Gain hands-on experience by building a data warehouse from scratch using PostgreSQL.

• Design and create a DWH schema based on a real-world scenario (e.g., sales analysis).

• Implement ETL processes to extract, transform, and load data into your DWH.

Module 7: Slowly Changing Dimensions (SCDs) (Week 4)

• Understand the concept of slowly changing dimensions (SCDs) and their importance in DWHs.

• Learn different SCD strategies like Type 1, Type 2, and Overlapping Dimensions.

• Implement SCD techniques in your PostgreSQL DWH to maintain data integrity.

Module 8: ELT vs. ETL: Choosing the Right Approach using Pentaho (Week 4)

• Explore the differences between Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes.

• Discuss the advantages and disadvantages of each approach for data warehousing.

• Choose the best approach (ETL or ELT) based on your specific data warehouse requirements.

Module 9: Connecting & Utilizing Your Data Warehouse (Week 4-5)

• Learn how to connect data visualization tools and business intelligence platforms to your DWH.

• Analyze data from your DWH to generate reports and uncover valuable insights through Power BI

   

This comprehensive syllabus provides a structured learning path for building data warehouses in PostgreSQL. It covers both theoretical knowledge and practical application, ensuring you can confidently design, develop, and manage data warehouses to unlock the power of data within your organization.