IBM Data Warehouse Engineer Professional Certificate Course Syllabus

A comprehensive and practical program that effectively prepares learners for entry-level roles in data warehousing and business intelligence. This certificate consists of five core courses and a final capstone project, designed to be completed in approximately 14 weeks with a commitment of about 10 hours per week. Learners will progress through foundational data engineering concepts to advanced data warehousing and analytics, gaining hands-on experience with industry-standard tools such as MySQL, PostgreSQL, Apache Airflow, Kafka, and Cognos Analytics. The curriculum emphasizes real-world projects that build a professional portfolio, culminating in a final project that integrates all learned skills.

Module 1: Introduction to Data Engineering

Estimated time: 30 hours

• Understand the data engineering ecosystem and lifecycle
• Explore various data repositories and data processing systems
• Learn about data ingestion, transformation, and loading processes
• Identify the role and responsibilities of a data engineer

Module 2: Relational Database Management Systems (RDBMS)

Estimated time: 30 hours

• Learn to design and implement relational databases
• Compose and execute SQL queries to retrieve and manipulate data
• Understand normalization and database design principles
• Work with MySQL, PostgreSQL, and IBM Db2

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

Estimated time: 40 hours

• Use shell scripts to automate data processing tasks
• Implement workflows using Apache Airflow
• Stream data using Apache Kafka
• Create and manage ETL pipelines for data integration

Module 4: Data Warehousing and BI Analytics

Estimated time: 40 hours

• Design and populate data warehouses
• Utilize business intelligence tools like Cognos Analytics
• Create reports and dashboards for data visualization
• Analyze data to extract actionable insights

Module 5: Capstone Project

Estimated time: 30 hours

• Design a complete data warehouse architecture
• Build and automate ETL pipelines using Airflow and shell scripts
• Populate the warehouse with transformed data and generate insights using Cognos Analytics

Module 6: Final Project

Estimated time: 20 hours

• Deliverable 1: A fully documented data warehouse schema
• Deliverable 2: Functional ETL pipelines processing sample business data
• Deliverable 3: Interactive dashboards and reports in Cognos Analytics

Prerequisites

• Basic computer literacy
• Some prior familiarity with IT concepts is beneficial
• No prior programming or data engineering experience required

What You'll Be Able to Do After

• Design and implement relational databases using SQL
• Create and manage ETL pipelines with Apache Airflow and shell scripting
• Stream and process data using Apache Kafka
• Design and populate data warehouses for business intelligence
• Generate insights and visualizations using Cognos Analytics