Data Warehousing for Business Intelligence Specialization course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Foundations of Data Warehousing
Estimated time: 12 hours
- Understand data warehouse architecture
- Learn differences between OLTP and OLAP systems
- Explore enterprise data management concepts
- Study data integration strategies
Module 2: Dimensional Modeling and Schema Design
Estimated time: 12 hours
- Learn star and snowflake schema design
- Understand fact and dimension tables
- Explore data normalization vs. denormalization
- Design scalable data models
Module 3: ETL and Data Integration
Estimated time: 12 hours
- Understand ETL workflow components
- Design data transformation pipelines
- Handle data cleansing and validation
- Automate data ingestion processes
Module 4: Data Warehouse Implementation and Analytics
Estimated time: 10 hours
- Optimize warehouse performance
- Integrate BI tools and dashboards
- Apply SQL queries for reporting
Module 5: Capstone Project
Estimated time: 16 hours
- Design a complete data warehouse architecture
- Implement dimensional modeling and ETL pipelines
- Generate analytical reports using BI tools
Prerequisites
- Familiarity with basic SQL
- Understanding of relational databases
- Fundamental knowledge of data management concepts
What You'll Be Able to Do After
- Design enterprise-scale data warehouse architectures
- Model data using star and snowflake schemas
- Build and automate ETL pipelines for data integration
- Optimize data warehouses for analytical performance
- Integrate BI tools to deliver actionable insights