Mastering Data Integration (ETL) with IBM DataStage

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

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Course curriculum

1. Introduction
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2. Outline of the course
  FREE PREVIEW
3. Get the materials
1. The agenda of the session
2. Data Integration in Data management
3. Some concepts and kinds of Data Integration
  FREE PREVIEW
4. What does data integration look like?
  FREE PREVIEW
1. The agenda of this session
2. Introduction to IBM Information Server
3. Introduction to IBM Information Server (cont.)
4. Key IBM Information Server Components
  FREE PREVIEW
5. IBM Information Server topology
  FREE PREVIEW
6. IBM Information Server topology (Cont.)
  FREE PREVIEW
1. The agenda of this session
2. IBM Information Server Administration Console
  FREE PREVIEW
3. IBM Information Server Administration Console (Cont.)
4. Real Practice 1 – IBM Information Server Administration Console
1. The agenda of this session
2. DataStage Architecture
3. DataStage Administrator
4. DataStage Designer
  FREE PREVIEW
5. DataStage Director
1. The agenda of this session
2. Developing in DataStage
3. DataStage project repository
4. Types of DataStage Jobs
5. Design Elements of Parallel Jobs
6. Partition Parallelism
7. Multi-Node Partitioning
8. Job design versus execution
9. Configuration File
10. Configuration File (Cont.)
11. Checkpoint - Developing in IBM DataStage and Features
12. Summary - Developing in IBM DataStage and Features
1. The agenda of this session
2. Unit Objectives - DataStage Administration
3. Information Server Web Console - Administration
4. Web Console Login Window
  FREE PREVIEW
5. User and Group Management
6. Creating a DataStage User ID
7. Assign DataStage Roles
8. DataStage Credentials
9. DataStage Credentials Default Mapping
10. Logging onto DataStage Administrator
11. InforSphere DataStage Administration
12. DataStage Administrator Tabs
13. Environment variables
14. Environment reporting variables
15. DataStage Administrator Permissions tab
16. Add users and groups
17. Specify DataStage Role
18. DataStage Administrator Logs Tab
19. DataStage Administrator Parallel Tab
20. Checkpoint - DataStage Administration
21. Real Practice 2 - Task 1 - Information Server Administration - User & Group
22. Real Practice 2 - Task 2 - Project Properties - General
23. Real Practice 2 - Task 3 - Project Properties - Environment
24. Real Practice 2 - Task 4 - Project Properties - User & Group
25. Summary - DataStage Administration
1. The agenda of this session
2. Unit Objectives - Work with metadata
3. Logging onto DataStage Designer
4. DataStage Designer
5. DataStage project repository
6. Import and Export
7. Exporting DataStage Components
8. Export objects
9. Import Procedure
10. Import objects
11. Checkpoint - Work with metadata
12. Real Practice 3 - Export & Import DataStage Components
13. Summary - Work with metadata
1. The agenda of this session
2. Unit objectives - Create parallel jobs
3. What is a parallel job?
4. Tools Palette
5. Create a new parallel job
6. Drag stages and links from the Palette
7. Rename links and stages
8. Connection Properties
9. Job parameters
10. Define a job parameter
11. Use a job parameter in a stage
12. Add job documentation
13. Job Properties window documentation
14. Compile and run a job
15. Compile, Errors or Successful message
16. DataStage Director
17. Run options
18. Performance statistics
19. Director Status View
20. Job log, viewed from designer
21. Other job log functions
22. Director monitor
23. Run jobs from the command line
24. Parameter sets
25. Create a parameter set
26. Defining the parameters
27. Defining values files
28. Load a parameter set into a job
29. Use parameter set parameters
30. Run jobs with parameter set parameters
31. Checkpoint - Create parallel jobs
32. Real Practice 4 - Task 1 - Database --> Transformer --> Database
33. Summary - Create parallel jobs
34. Real Practice 4 - Task 2 - Database --> Transformer --> Database with Parameter
1. The agenda of this session
2. Unit objectives - Access sequential data
3. How sequential data is handled
4. Features of the Sequential File stage
5. Job design with Sequential File Stages
6. Sequential File stage properties
7. Format Tab
8. Column Tab
9. Multiple Readers
10. Writing to a sequential file
11. Reject links
12. Source and target reject links
13. Setting the Reject Mode property
14. Checkpoint - Access sequential data
15. Real Practice 5 - Task 1 - File --> Transformer --> File
16. Real Practice 5 - Task 2 - File --> Transformer --> DataSet with Parameter
17. Real Practice 6 - File --> Transformer --> DataSet
18. Summary - Access sequential data
1. The agenda of this session
2. Unit objectives - Partitioning and collecting algorithms
3. Partition parallelism
4. Stage partitioning
5. DataStage hardware environments
6. Partitioning algorithms
7. Collecting
8. Collecting (Cont.)
9. Collecting algorithms
10. Keyless versus keyed partitioning algorithms
11. Round Robin and Random partitioning
12. Entire partitioning
13. Hash partitioning
14. Modulus partitioning
15. Auto partitioning
16. Partitioning / collecting link icons
17. More partitioning icons
18. Specify a partitioning algorithm
19. Specify a collecting algorithm
20. Configuration file
21. Example configuration file
22. Adding $APT_CONFIG_FILE as a job parameter
23. Editing configuration files
24. Checkpoint - Partitioning and collecting algorithms
25. Summary - Partitioning and collecting algorithms
1. The agenda of this session
2. Unit objectives - Combine Data
3. Combine Data
4. Lookup, Join, Merge stages
5. Lookup Stage features
6. Lookup types
7. Match Lookup Stage Example
8. Lookup Stage with an equality match
9. Define the Lookup key
10. Specify the output columns
11. Lookup failure actions
12. Specifying lookup failure actions
13. Lookup stage with reject link
14. Real Practice 7 - Task 1 - Combine data with Lookup Stage
15. Join stage
16. Job with Join Stage
17. Join Stage Properties
18. Output Mapping tab
19. Merge stage
20. Merge Stage Job
21. Merge Stage Properties
22. Funnel stage
23. Funnel Stage Example
24. Funnel Stage Properties
25. Checkpoint - Combine Data
26. Real Practice 7 - Task 2 - Combine data with Join Stage
27. Real Practice 7 - Task 3 - Combine Data with Merge Stage
28. Real Practice 7 - Task 4 - Combine Data with Funnel Stage
29. Summary - Combine Data
1. The agenda of this session
2. Unit objectives - Group processing stages
3. Group processing stages
4. Sort data
5. Sorting alternatives
6. In-Stage sorting
7. Sort Stage Properties tab
8. Specify sort keys
9. Partition sorts
10. Aggregator stage
11. Job with Aggregator Stage
12. Aggregation types
13. Aggregation types (Cont.)
14. Output Mapping Tab
15. Output Columns tab
16. Calculation aggregation type
17. Grouping methods
18. Remove duplicates
19. Remove Duplicates stage job
20. Remove Duplicates stage properties
21. Fork - Join Job Design
22. Checkpoint - Group processing stages
23. Real Practice 8 - File --> Transformer --> DataSet --> Aggregator --> File
24. Summary - Group processing stages
1. The agenda of this session
2. Unit Objectives - Transformer stage
3. Transformer stage
4. Job with a Transformer stage
5. Inside the Transformer stage
6. Transformer stage elements
7. Transformer stage elements
8. Constraints
9. Constraints example
10. Define a constraint
11. Use the expression editor
12. Otherwise links for data integrity
13. Real Practice 9 - File --> Transformer --> File
14. Parallel job debugger
15. Set breakpoints
16. Edit breakpoints
17. Running a parallel job in the debugger
18. Add columns to the watch list
19. Checkpoint - Transformer stage
20. Checkpoint - Transformer stage
1. The agenda of this session
2. Unit objectives - Repository functions
3. Quick find
4. Found results
5. Advanced Find window
6. Advanced Find options
7. Using the found results
8. Performing an impact analysis
9. Initiating an impact analysis
10. Results in text format
11. Results in graphical format
12. Displaying the dependency graph
13. Displaying the dependency path
14. Viewing column-level data flow
15. Finding where a column originates
16. Displayed results
17. Finding the difference between two jobs
18. Initiating the comparison
19. Comparison results
20. Saving to an HTML file
21. Checkpoint - Repository functions
22. Summary - Repository functions
1. The agenda of this session
2. Unit Objectives - Work with relational data
3. Connector stages
4. Reading from database tables
5. Connector stage GUI
6. Navigation panel
7. Connection properties
8. Usage properties - Session and Before/After SQL
9. Writing to database tables
10. DB2 Connector GUI
11. Connector write properties
12. Data connection objects
13. Data connection objects
14. Creating a new data connection object
15. Real Practice 11 - Relational Database --> Transformer --> File
16. Summary - Work with relational data
1. The agenda of this session
2. Unit Objectives - Job Sequence control
3. What is a job sequence?
4. Basics for creating a job sequence
5. Job sequence stages
6. Job sequence example
7. Job Activity stage properties
8. Job Activity trigger
9. Execute Command stage
10. Notification Activity stage
11. User Variables stage
12. Wait for File stage
13. Sequencer stage
14. Nested Condition stage
15. Loop stages
16. Checkpoint - Job control
17. Summary - Job control
1. The agenda of this session
2. Demonstration12 (Real Practice 12 - AWS Cloud Data Integration with IBM DataStage S3 Connector)
3. Real Practice 12 - AWS Cloud Data Integration with IBM DataStage S3 Connector
1. Data Vault Introduction
  FREE PREVIEW
2. Data Vault Integration with IBM DataStage
  FREE PREVIEW
3. Real Practice 13 - Mini Project 1 - Data Vault 1.0 DWH with IBM DataStage
4. Real Practice 13 - Mini Project 2 - Data Vault 2.0 DWH with IBM DataStage
1. Summary
1. Special Gift for You

About this course

$26.00
286 lessons
6 hours of video content

Mastering Data Integration (ETL) with IBM DataStage

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

What You’ll Learn

📚 Foundations of Data Integration

Core concepts and types of data integration, with real-world examples.
Overview of IBM Information Server and its role in data integration.

🖥️ IBM DataStage Administration & Navigation

Learn to use the IBM Information Server Administration Console.
Master DataStage architecture and practical administration tasks.

🔄 Hands-On IBM DataStage Development

Practical project creation, job types, and parallel processing with DataStage.
Work with metadata management and hands-on parallel job creation.

🔗 Advanced Data Processing

Sequential data handling using the Sequential File stage.
Implement partitioning and collecting algorithms for efficient data processing.

🔍 Combining Data with Stages

Work with Lookup, Join, Merge, and Funnel stages for real-world data combination.
Apply group processing techniques such as sorting, deduplication, and aggregation.

🔧 Data Transformation & Repository Functions

Master the Transformer stage for data manipulation and transformation.
Explore repository functions, job comparisons, and impact analysis.

🌐 Cloud Integration & Data Vault Practice

Real-world integration with AWS Cloud services.
Practical exercises in Data Vault 1.0 & 2.0 integration.

Requirements

📘 Prior Knowledge

Basic understanding of data concepts (data sources, data transformation, etc.).
Optional: Familiarity with SQL and access to IBM DataStage software for hands-on practice.
A strong desire to learn data integration concepts and skills.

Course Overview

In this course, you will unlock the potential of IBM DataStage, an industry-leading ETL tool. Begin with data integration basics and progress to advanced techniques, gaining hands-on experience in DataStage administration, job sequencing, and real-world data integration practices with AWS and Data Vault.

Course Objectives

Grasp Data Integration Fundamentals: Understand the essential concepts and applications.
Master IBM DataStage Administration: Navigate administration tasks, manage users, and set permissions.
Develop Advanced Parallel Jobs: Create efficient parallel jobs, access sequential data, and implement partitioning.
Transform Data with Stages: Utilize Lookup, Join, Merge, Funnel, and Transformer stages for comprehensive data processing.
Apply Cloud & Data Vault Integration: Practice integrating Data Vault and AWS Cloud services for real-world application.

Who This Course is For

Data Professionals: Enhance your integration skills using IBM DataStage.
IT Professionals: Expand your data integration expertise with advanced features.
Business Analysts: Understand how data integration impacts decision-making.
Students & Graduates: Build a strong foundation in data integration for future opportunities.
IBM DataStage Users: Deepen your knowledge and improve job performance.

Join us in Mastering Data Integration with IBM DataStage to expand your data capabilities and become proficient in modern data integration techniques!

Reference, Rating, and Feedback

The same Udemy course can be found at this link:

https://www.udemy.com/course/mastering-data-integration-with-ibm-datastage/?referralCode=8451B9E0DB93C0C70F46

Instructor(s)

Instructor Bio:

I'm a seasoned author deeply passionate about data strategy and management. With over 15 years in IT, spanning banking, insurance, and retail, I've held key roles such as Data Division Director and Chief Data Officer. Currently, as Director of Data Division, I shape data initiatives, while as a Governance & Analytics expert, I establish robust frameworks. Through my writing, I share practical strategies and insights honed from diverse industry experience.

Dien Pham Cong

Chief Data Officer

[email protected]

Instructor(s)

Instructor Bio:

Discover your potential, starting today

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Mastering Data Integration (ETL) with IBM DataStage

Course curriculum

1. Introduction to Data Integration

2. Data Integration in Data management

3. Introduction to IBM Information Server

4. IBM Information Server Administration Console

5. Introduction to IBM DataStage

6. Developing in DataStage and Features

7. DataStage Administration

8. Work with metadata

9. Create Parallel Job

10. Create parallel jobs - Access sequential data

11. Partitioning and collecting algorithms

12. Combine Data

13. Group processing stages

14. Transformer Stage

15. Repository functions

16. Work with relational data

17. Job Sequence Control

18. AWS Cloud Integration

19. Data Vault 1.0 & 2.0 Integration

20. Summary

Special Gift for You

About this course

Mastering Data Integration (ETL) with IBM DataStage

What You’ll Learn

Requirements

Course Overview

Course Objectives

Who This Course is For

Reference, Rating, and Feedback

Instructor(s)

Dien Pham Cong

Instructor(s)

Discover your potential, starting today

Subscribe to our Newsletter!