IBM InfoSphere DataStage v11.5 - Advanced Data Processing

This course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you, will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course.

View Entire Schedule

Use Connector stages to read from and write to database tables
Handle SQL errors in Connector stages
Use Connector stages with multiple input links
Use the File Connector stage to access Hadoop HDFS data
Optimize jobs that write to database tables
Use the Unstructured Data stage to extract data from Excel spreadsheets
Use the Data Masking stage to mask sensitive data processed within a DataStage job
Use the Hierarchical stage to parse, compose, and transform XML data
Use the Schema Library Manager to import and manage XML schemas
Use the Data Rules stage to validate fields of data within a DataStage job
Create custom data rules for validating data
Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions

Viewing outline for:

Classroom Live Outline

1. Accessing Databases

Connector Stage Overview
Connector Stage Functionality
Error Handling in Connector Stages
Multiple Input Links
File Connector Stage
Handling Database Error
Parallel jobs with Multiple Connector Input Links
Using the File Connector Stage to Read and Write HDFS Files

2. Processing Unstructured Data

Using the Unstructured Data Stage in DataStage Jobs
Extract Data from an Excel Spreadsheet
Specify a Data Range for Data Extraction in an Unstructured Data Stage
Specify Document Properties for Data Extraction
Processing Unstructured Data

3. Data Masking

Using the Data Masking stage in DataStage jobs
Data Masking Techniques
Data Masking Policies
Applying Policies for Masquerading Context-Aware Data Types
Applying Policies for Masquerading Generic Data Types
Repeatable Replacement
Using Reference Tables
Creating Custom Reference Tables
Data Masking

4. Using Data Rules

Introduction to Data Rules
Using the Data Rules Editor
Selecting Data Rules
Binding Data Rule Variables
Output Link Constraints
Adding Statistics and Attributes to the Output Information
Use the Data Rules Stage to Valid Foreign Key References in Source Data
Create Custom Data Rules
Using Data Rules

5. Processing XML Data

Introduction to the Hierarchical Stage
Hierarchical Stage Assembly Editor
Use the Schema Library Manager to Import and Manage XML Schemas
Composing XML Data
Using the HJoin Step to Create Parent-Child Relationships between Input Lists
Using the Composer Step
Writing Hierarchical Data to a Relational Table
Using the Regroup Step
Consuming XML Data
Using the XML Parser Step
Propagating Columns
Transforming XML Data
Using the Aggregate Step
Using the Sort Step
Using the Switch Step
Using the H-Pivot Step
Importing XML Schemas
Compose Hierarchical Data
Consume Hierarchical Data
Transform Hierarchical Data

6. Updating a Star Schema Database

Surrogate Keys
Design a Job that Creates and Updates a Surrogate Key Source Key File from a Dimension Table
Slowly Changing Dimensions (SCD) Stage
Star Schema Databases
SCD Stage Fast Path Pages
Specifying Purpose Codes
Dimension Update specification
Design a Job that Processes a Star Schema Database with Type 1 and Type 2 Slowly Changing Dimensions
Build a Parallel Job that Updates a Star Schema Database with Two Dimensions

1. Accessing Databases

Connector Stage Overview
Connector Stage Functionality
Error Handling in Connector Stages
Multiple Input Links
File Connector Stage
Handling Database Error
Parallel jobs with Multiple Connector Input Links
Using the File Connector Stage to Read and Write HDFS Files

2. Processing Unstructured Data

Using the Unstructured Data Stage in DataStage Jobs
Extract Data from an Excel Spreadsheet
Specify a Data Range for Data Extraction in an Unstructured Data Stage
Specify Document Properties for Data Extraction
Processing Unstructured Data

3. Data Masking

Using the Data Masking stage in DataStage jobs
Data Masking Techniques
Data Masking Policies
Applying Policies for Masquerading Context-Aware Data Types
Applying Policies for Masquerading Generic Data Types
Repeatable Replacement
Using Reference Tables
Creating Custom Reference Tables
Data Masking

4. Using Data Rules

Introduction to Data Rules
Using the Data Rules Editor
Selecting Data Rules
Binding Data Rule Variables
Output Link Constraints
Adding Statistics and Attributes to the Output Information
Use the Data Rules Stage to Valid Foreign Key References in Source Data
Create Custom Data Rules
Using Data Rules

5. Processing XML Data

Introduction to the Hierarchical Stage
Hierarchical Stage Assembly Editor
Use the Schema Library Manager to Import and Manage XML Schemas
Composing XML Data
Using the HJoin Step to Create Parent-Child Relationships between Input Lists
Using the Composer Step
Writing Hierarchical Data to a Relational Table
Using the Regroup Step
Consuming XML Data
Using the XML Parser Step
Propagating Columns
Transforming XML Data
Using the Aggregate Step
Using the Sort Step
Using the Switch Step
Using the H-Pivot Step
Importing XML Schemas
Compose Hierarchical Data
Consume Hierarchical Data
Transform Hierarchical Data

6. Updating a Star Schema Database

Surrogate Keys
Design a Job that Creates and Updates a Surrogate Key Source Key File from a Dimension Table
Slowly Changing Dimensions (SCD) Stage
Star Schema Databases
SCD Stage Fast Path Pages
Specifying Purpose Codes
Dimension Update specification
Design a Job that Processes a Star Schema Database with Type 1 and Type 2 Slowly Changing Dimensions
Build a Parallel Job that Updates a Star Schema Database with Two Dimensions

1. Accessing Databases

Connector Stage Overview
Connector Stage Functionality
Error Handling in Connector Stages
Multiple Input Links
File Connector Stage
Handling Database Error
Parallel jobs with Multiple Connector Input Links
Using the File Connector Stage to Read and Write HDFS Files

2. Processing Unstructured Data

Using the Unstructured Data Stage in DataStage Jobs
Extract Data from an Excel Spreadsheet
Specify a Data Range for Data Extraction in an Unstructured Data Stage
Specify Document Properties for Data Extraction
Processing Unstructured Data

3. Data Masking

Using the Data Masking stage in DataStage jobs
Data Masking Techniques
Data Masking Policies
Applying Policies for Masquerading Context-Aware Data Types
Applying Policies for Masquerading Generic Data Types
Repeatable Replacement
Using Reference Tables
Creating Custom Reference Tables
Data Masking

4. Using Data Rules

Introduction to Data Rules
Using the Data Rules Editor
Selecting Data Rules
Binding Data Rule Variables
Output Link Constraints
Adding Statistics and Attributes to the Output Information
Use the Data Rules Stage to Valid Foreign Key References in Source Data
Create Custom Data Rules
Using Data Rules

5. Processing XML Data

Introduction to the Hierarchical Stage
Hierarchical Stage Assembly Editor
Use the Schema Library Manager to Import and Manage XML Schemas
Composing XML Data
Using the HJoin Step to Create Parent-Child Relationships between Input Lists
Using the Composer Step
Writing Hierarchical Data to a Relational Table
Using the Regroup Step
Consuming XML Data
Using the XML Parser Step
Propagating Columns
Transforming XML Data
Using the Aggregate Step
Using the Sort Step
Using the Switch Step
Using the H-Pivot Step
Importing XML Schemas
Compose Hierarchical Data
Consume Hierarchical Data
Transform Hierarchical Data

6. Updating a Star Schema Database

Surrogate Keys
Design a Job that Creates and Updates a Surrogate Key Source Key File from a Dimension Table
Slowly Changing Dimensions (SCD) Stage
Star Schema Databases
SCD Stage Fast Path Pages
Specifying Purpose Codes
Dimension Update specification
Design a Job that Processes a Star Schema Database with Type 1 and Type 2 Slowly Changing Dimensions
Build a Parallel Job that Updates a Star Schema Database with Two Dimensions

Viewing labs for:

Classroom Live Labs

• VMWare-based
• All x86/x64 VMWare training per person

IBM InfoSphere DataStage Essentials (v11.5)

• Experienced DataStage developers who want learn about more advanced DataStage job techniques

Cart () Loading...

Subtotal

IBM InfoSphere DataStage v11.5 - Advanced Data Processing

Course Overview

Schedule

What You'll Learn

Outline

Classroom Live Outline

Labs

Classroom Live Labs

Prerequisites

Who Should Attend

Course Delivery