Course Overview / Audience / Prerequisites / Topics

Course Overview

This course is designed for beginners in DataStage as well as for those who have worked int DataStage thick client. It begins with introducing the new interface for DataStage: the DataStage Flow. The course covers commonly used stages, cloud connecters and advanced connectors available in DataStage on IBM Cloud Pak for Data (CP4D). 

The course has Lab Exercises for the Units.

Audience

Prerequisites

• Understanding of Databases and ETL
• Basic Familiarity with Cloud services.

Topics

Day 1 

1. Unit 1: Overview of Cloud Pak for Data
   • Introduction of CP4D
     • Login
     • Home Page
     • Profile and Settings
     • Services Catalog
   • CP4D Architecture

2. Unit 2: Transforming Data using DataStage on CP4D
   • Create DataStage Project
   • Create DataStage Parallel Job
   • Save and Compile DataStage Job
   • Run and monitor DataStage job
   • Configuration Files for DataStage on CP4D
   • Import and Export DataStage job
   • Add Environment Variables
   • Job run settings.
   • Asset browser
   • Export and Import Project
   • Clone a job
3. Unit 3: Processing Stages
   1. Merge Stage
   2. Join Stage
   3. Sort Stage
   4. Transformer Stage
   5. Remove Duplicates Stage

Day 2 

4. Unit 4: Amazon S3 Connector
5. Unit 5: Amazon RedShift Connector
6. Unit 6: Microsoft Azure Connector

Day 3

7. Unit 7: Google Big Query Connector
8. Unit 8: Snowflake Connector
9. Unit 9: Checksum Stage

Day 4

10. Unit 10: Change Capture and Change Apply
11. Unit 11: Dataset
12. Unit 12: HTTP Connector
13. Unit 13: ODBC Connector
14. Unit 14: Compress
15. Unit 15: Expand
16. Unit 16: Decode
17. Unit 17: Encode

Day 5

18. Administration:
    1. Cluster administration
       • Scaling services
       • Add nodes to your Cloud Pak for Data cluster
       • Backup and restore your deployment
         1. Backup and restore service list
         2. Backing up and restoring an entire deployment
         3. Backing up and restoring volumes
         4. Migrating Cloud Pak for Data metadata and clusters

2. Cloud Pak for Data platform administration
   • Managing users
     • Connecting to your identity provider
     • Predefined roles and permissions
     • Managing roles and user groups
   • Importing JDBC drivers for data sources
   • Monitoring the platform
   • Managing storage volumes
   • Gathering diagnostic information
   • Customizing the platform