Mastering Data Integration (ETL) with IBM DataStage

Goals

• Fundamentals of Data Integration: Understand the core concepts and types of data integration and explore real-world examples.
• Navigating IBM Information Server: Get acquainted with the components of IBM Information Server and its role in data integration.
• IBM Information Server Administration: Learn to navigate the IBM Information Server Administration Console and practice essential administrative tasks.
• Exploring IBM DataStage: Dive into the architecture of IBM DataStage, its key components, and practical uses
• Developing in IBM DataStage: Work hands-on in DataStage, create projects, explore job types, and utilize design elements for parallel processing.
• DataStage Administration: Acquire practical skills in DataStage administration, including user management, permissions, and environment variables.
• Metadata Management: Practice metadata management using DataStage Designer, importing, and exporting components.
• Creating Parallel Jobs: Engage in practical sessions to create parallel jobs, define parameters, and document your jobs effectively.
• Accessing Sequential Data: Hands-on experience in handling sequential data, utilizing the Sequential File stage, and managing reject links.
• Implementing Partitioning and Collecting Algorithms: Gain practical insights into partition parallelism, partitioning algorithms, and collecting strategies.
• Combining Data with Stages: Work with Lookup, Join, Merge, and Funnel stages, and practice their applications in real-world scenarios.
• Group Processing Stages: Learn to sort data effectively, remove duplicates, and utilize Aggregator stages in practical exercises.
• Transforming Data: Practice using the Transformer stage, constraints, and debugging techniques for data transformation.
• Repository Functions: Explore practical aspects of using the repository, finding differences between jobs, and performing impact analyses.
• Working with Relational Data: Engage in hands-on activities involving connector stages, reading and writing to database tables, and utilizing data connection ob
• Job Sequence Control: Gain practical experience in creating job sequences, defining triggers, and managing job activities through various stages.
• Real Practice: AWS Cloud Integration: Apply your skills to integrate data with AWS Cloud services in real-world scenarios.
• Real Practice: Data Vault 1.0 & 2.0 Integration: Practical exercises in integrating Data Vault concepts into your data integration projects.

Prerequisites

• Basic Understanding of Data Concepts: A fundamental grasp of data concepts is recommended. Students should understand terms like data sources, data transformation, and data loading.
• SQL Knowledge (Optional): While not mandatory, having some familiarity with SQL (Structured Query Language) can be beneficial, especially when working with relational databases.
• Access to IBM DataStage: Ideally, students should have access to IBM DataStage software to practice and follow along with the course.
• IBM DataStage Software (Optional): If students want to practice the skills learned in the course, having access to IBM DataStage software is beneficial
• Desire to Learn: A genuine interest in data integration and a willingness to learn and practice the concepts taught in the course are essential.