Data Ingestion, Extraction & Transformation (ETL/ELT in BI)

Discipline: Data Analyst | Module: Module 3: Business Intelligence (BI), Data Modeling & Enterprise Dashboarding | Estimated Study Time: 16 Hours

Welcome to Data Ingestion, Extraction & Transformation (ETL/ELT in BI). This topic delivers foundational and advanced concepts designed for production engineering and real-world workflows.

Key Learning Objectives

1. Power Query / Tableau Prep (GUI-driven M-Language transformations)
2. Schema Modeling (Star Schema, Snowflake Schema, Fact Tables vs. Dimension Tables)
3. Dimensional Design (Slowly Changing Dimensions - SCD Type 1, Type 2, Type 3)

Detailed Curriculum Breakdown

Power Query / Tableau Prep (GUI-driven M-Language transformations)

Explore the fundamental principles, real-world patterns, and best practices for Power Query / Tableau Prep (GUI-driven M-Language transformations). Practice hands-on implementations to master these concepts.

// Code Example: Power Query / Tableau Prep (GUI-driven M-Language transformations)
// Implement verified patterns for production use
console.log("Mastering Power Query / Tableau Prep (GUI-driven M-Language transformations)");

Schema Modeling (Star Schema, Snowflake Schema, Fact Tables vs. Dimension Tables)

Explore the fundamental principles, real-world patterns, and best practices for Schema Modeling (Star Schema, Snowflake Schema, Fact Tables vs. Dimension Tables). Practice hands-on implementations to master these concepts.

// Code Example: Schema Modeling (Star Schema, Snowflake Schema, Fact Tables vs. Dimension Tables)
// Implement verified patterns for production use
console.log("Mastering Schema Modeling (Star Schema, Snowflake Schema, Fact Tables vs. Dimension Tables)");

Dimensional Design (Slowly Changing Dimensions - SCD Type 1, Type 2, Type 3)

Explore the fundamental principles, real-world patterns, and best practices for Dimensional Design (Slowly Changing Dimensions - SCD Type 1, Type 2, Type 3). Practice hands-on implementations to master these concepts.

// Code Example: Dimensional Design (Slowly Changing Dimensions - SCD Type 1, Type 2, Type 3)
// Implement verified patterns for production use
console.log("Mastering Dimensional Design (Slowly Changing Dimensions - SCD Type 1, Type 2, Type 3)");

Practical Application & Exercises

1. Architecture Review: Evaluate how Data Ingestion, Extraction & Transformation (ETL/ELT in BI) integrates with upstream and downstream systems.
2. Implementation Challenge: Build a functional prototype demonstrating each of the subtopics.
3. Validation & Testing: Verify performance and error handling under edge-case scenarios.

Summary Checklist

• Studied foundational architecture for Data Ingestion, Extraction & Transformation (ETL/ELT in BI)
• Completed practical coding challenge
• Validated edge cases and error handling routines