Mastering Data Integration (ETL) with IBM DataStage

Name: Mastering Data Integration (ETL) with IBM DataStage
Rating: 3.6 (70 reviews)

Unlock the Power of Data Integration (ETL): Practical Training with IBM DataStage (ETL)

Created byDien Pham, Quan Pham, Cu Dinh Tien, Educonnhub

Last updated 4/2025

English

What you'll learn

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.

Course content

20 sections • 273 lectures • 5h 57m total length

Introduction2:52
Outline of the course5:03
Get the materials0:04

The agenda of this session1:27
Unit Objectives - DataStage Administration0:44
Information Server Web Console - Administration1:15
Web Console Login Window1:09
User and Group Management1:33
Creating a DataStage User ID0:43
Assign DataStage Roles0:32
DataStage Credentials1:12
DataStage Credentials Default Mapping0:48
Set up DataStage credentials by opening the engine credentials, selecting the DataStage server, and entering OS user IDs and passwords. Map information server IDs to DataStage IDs for tighter access.
Logging onto DataStage Administrator0:34
InforSphere DataStage Administration0:56
DataStage Administrator Tabs0:22
Environment variables0:48
Environment reporting variables0:33
DataStage Administrator Permissions tab0:46
Add users and groups0:20
Specify DataStage Role0:46
DataStage Administrator Logs Tab0:30
DataStage Administrator Parallel Tab1:02
Checkpoint - DataStage Administration
Real Practice 2 - Task 1 - Information Server Administration - User & Group3:03
Real Practice 2 - Task 2 - Project Properties - General2:22
Real Practice 2 - Task 3 - Project Properties - Environment1:13
Real Practice 2 - Task 4 - Project Properties - User & Group0:59
Summary - DataStage Administration1:21

The agenda of this session2:06
Unit objectives - Create parallel jobs0:29
What is a parallel job?1:10
Tools Palette0:32
Create a new parallel job0:31
Drag stages and links from the Palette0:13
Rename links and stages0:30
Connection Properties0:43
Job parameters0:47
Define a job parameter0:32
Use a job parameter in a stage0:19
Add job documentation0:15
Job Properties window documentation0:24
Compile and run a job0:30
Compile, Errors or Successful message0:17
DataStage Director0:43
Run options0:23
Performance statistics0:29
Director Status View0:21
Job log, viewed from designer0:33
Other job log functions0:39
Director monitor0:17
Run jobs from the command line0:27
Parameter sets0:43
Create a parameter set0:08
Defining the parameters0:29
Defining values files0:34
Load a parameter set into a job0:23
Use parameter set parameters0:17
Run jobs with parameter set parameters0:22
Checkpoint - Create parallel jobs
Real Practice 4 - Task 1 - Database --> Transformer --> Database3:36
Real Practice 4 - Task 2 - Database --> Transformer --> Database with Parameter3:27
Summary - Create parallel jobs1:28

The agenda of this session1:39
Unit objectives - Access sequential data0:51
How sequential data is handled0:52
Features of the Sequential File stage0:38
Job design with Sequential File Stages0:45
Sequential File stage properties0:59
Format Tab0:38
Column Tab0:44
Multiple Readers0:48
Writing to a sequential file0:49
Reject links0:42
Configure reject links on source or target sequential file stages to capture rows rejected by metadata or format issues, and set the reject mode to avoid compile errors.
Source and target reject links0:27
Setting the Reject Mode property0:18
Checkpoint - Access sequential data
Real Practice 5 - Task 1 - File --> Transformer --> File3:45
Real Practice 5 - Task 2 - File --> Transformer --> DataSet with Parameter2:42
Real Practice 6 - File --> Transformer --> DataSet2:32
Summary - Access sequential data1:19

Requirements

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.

Description

*This course contains the use of artificial intelligence.*

Unlock the power of data integration with IBM DataStage, the industry-leading ETL (Extract, Transform, Load) tool. In this comprehensive course, you'll embark on a journey from data integration basics to advanced techniques, empowering you to harness the full potential of your data.

What You'll Learn:

Foundations of Data Integration: Begin by understanding the core concepts and types of data integration, laying a strong foundation for your journey.
IBM Information Server: Explore the IBM Information Server ecosystem and its vital components to comprehend where DataStage fits in.
Hands-On Administration: Get hands-on with DataStage administration tasks, managing users, roles, and permissions with ease.
Mastering Metadata: Learn to work effectively with metadata, a crucial aspect of data integration, to streamline your processes.
Parallel Jobs Creation: Dive into parallel job creation, understand its intricacies, and design efficient parallel jobs.
Accessing Sequential Data: Master the art of accessing sequential data, a crucial skill in data integration.
Advanced Algorithms: Explore partitioning and collecting algorithms, vital for efficient data processing.
Combine Data Effectively: Get comfortable with stages like Lookup, Join, Merge, and Funnel to combine data seamlessly.
Group Processing Stages: Learn to group process data, sort it, and aggregate it effectively.
Transformer Stage: Dive deep into the Transformer stage and its capabilities for data transformation.
Repository Functions: Understand repository functions, impact analysis, and how to compare different jobs.
Relational Data Integration: Work with relational data using connector stages, read from and write to database tables.
Job Sequence Control: Master job sequencing, control the flow of jobs, and create complex workflows.
Real-world Practice: Apply your knowledge in real-world scenarios with practical AWS Cloud and Data Vault integration sessions.

Who this course is for:

Data Professionals: Data analysts, data engineers who want to enhance their data integration skills using IBM DataStage.
IT Professionals: IT specialists, software developers, and database administrators who need to work with data integration solutions.
Business Analysts: Business analysts who want to understand how data integration impacts their data-driven decision-making processes.
Students and Graduates: Students pursuing degrees or recent graduates looking to build a foundation in data integration and expand their job prospects.
IBM DataStage Users: Users of IBM DataStage looking to deepen their knowledge, explore advanced features, and improve their job performance.
Anyone Interested in Data Integration: If you have a general interest in data integration and want to learn how IBM DataStage can be used for these purposes, this course is suitable for you.

Mastering Data Integration (ETL) with IBM DataStage

What you'll learn

Explore related topics

Course content

Introduction to Data Integration3 lectures • 8min

Data Integration in Data management4 lectures • 9min

Introduction to IBM Information Server6 lectures • 14min

IBM Information Server Administration Console4 lectures • 5min

Introduction to IBM DataStage5 lectures • 6min

Developing in DataStage and Features11 lectures • 12min

DataStage Administration24 lectures • 25min

Work with metadata12 lectures • 11min

Create Parallel Job33 lectures • 25min

Create parallel jobs - Access sequential data17 lectures • 20min

Requirements

Description

Who this course is for: