Training / IBM DataStage on IBM Cloud Pak for Data
IBM DataStage on IBM Cloud Pak for Data
This course teaches how to use Data Refinery for self-service data preparation, Data profiling and Visualization. Users will also know how to manage and govern data assets in knowledge catalog. Users will gain experience by creating Governance artifacts and adding data assets to a governed catalog so that data protection rules are automatically enforced to protect sensitive data from unauthorized access. They will also learn how to quickly find and access data, self-service data request and fulfilling the Data request.
Audience:
Data Engineer, ETL Developer, Data Integration Specialist, Data Architect, Cloud Data Engineer
Objectives: This is a 4-day instructor-led course, conducted over 5 hours per day.
Overview
- Introduction to Cloud Pak for Data
- Introduction to DataStage
- Parallel Framework
Working with DataStage
- Projects
- Stages, Links and RCP
- Invocation Id’s
- Table Definitions
- DataStage Flow
- Compile and Run
- Adaptable Flows
- Subflows
- Multi-instance Jobs
- Import and Export flows
File Stages
- Sequential File Stage
- Data Set Stage
Data Processing Stages
- Sorting Data
- Sort Stage
- Remove Duplicates Stage
- Aggregator Stage
- Combining Data
- Lookup Stage
- Join Stage
- Merge Stage
Data Connector Stages (Choice of any two connectors)
- Oracle Connector Stage
- DB2 Connector Stage
- Teradata Connector Stage
- MySQL Connector Stage
- ODBC Connector Stage
Cloud Connector Stages (Choice of any two Cloud Connectors)
- Amazon S3 Connector
- Amazon RedShift Connector
- Microsoft Azure Connector for File Storage
- Microsoft Azure SQL Server Connector Stage
- Google Big Query Connector
- Snowflake Connector
Data Transformation Stages
- Transformer Stage
- Hierarchical Data Stage
Watson Pipeline
- Introduction
- Pipelines Nodes
- Trigger Conditions
- Handling Errors
- Run Pipelines