Course Description

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:

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