BI Foundations with SQL, ETL and Data Warehousing Specialization Course Syllabus

This specialization provides a comprehensive introduction to Business Intelligence (BI) and data engineering fundamentals, designed for beginners aiming to build a career in data. Over approximately 11 weeks of hands-on learning, you'll gain practical experience with core technologies including SQL, ETL processes, data warehousing, and workflow automation tools like Airflow and Kafka. Each module blends theory with real-world projects, enabling you to develop job-ready skills in data extraction, transformation, and analysis. The course concludes with a capstone project that integrates all learned concepts into a functional data pipeline and warehouse system.

Module 1: Introduction to Data Analytics and Business Intelligence

Estimated time: 6 hours

• Overview of Business Intelligence (BI) and its role in organizations
• Understanding the data analytics lifecycle
• Identifying key performance indicators (KPIs) and metrics
• Case-based analysis of BI applications in real businesses

Module 2: Getting Started with SQL for Data Analysis

Estimated time: 9 hours

• Writing basic SELECT statements for data retrieval
• Filtering and sorting data using WHERE, ORDER BY clauses
• Performing table joins to combine datasets
• Aggregating data using GROUP BY and functions like SUM, COUNT, AVG

Module 3: ETL and Data Pipelines with Shell, Airflow, and Kafka

Estimated time: 9 hours

• Introduction to ETL: Extract, Transform, Load concepts
• Scripting basics for data processing using shell scripts
• Orchestrating workflows with Apache Airflow
• Streaming data integration using Apache Kafka

Module 4: Data Warehousing and BI Analytics

Estimated time: 9 hours

• Designing star and snowflake schemas for data warehouses
• Understanding OLAP systems and multidimensional analysis
• Creating and managing data marts
• Implementing data governance and quality practices

Module 5: Hands-on Capstone Project

Estimated time: 10 hours

• Designing an end-to-end ETL pipeline
• Populating a mini data warehouse with transformed data
• Running analytical queries to generate business insights

Prerequisites

• Familiarity with basic computer operations and web applications
• No prior programming experience required
• Basic understanding of business operations helpful but not required

What You'll Be Able to Do After

• Master SQL for data extraction and transformation in business environments
• Understand and implement ETL processes using industry-standard tools
• Build and manage data warehouse systems using best practices
• Analyze business data to generate meaningful insights for decision-making
• Deploy automated data workflows using Airflow and Kafka