This course is not scheduled. Inquire about Onsite training at your facility.
Overview
| Course code | DX730 | Skill level | Basic |
|---|---|---|---|
| Duration | 4.0 days | Delivery type | Classroom
(Hands-on labs) |
| Course type | Public or Private on-site | ||
| Public price | USD $2,995.00 plus tax | ||
This course was formerly course number QS320.
Through group discussions, hands-on labs, and practice exercises, prepare for the real-world application of QualityStage and data integration methods. Throughout this course, use known data sets with known problems and solutions. To add value to your training experience, the instructor may opt to perform similar exercises with a sample of your project data.
Course Materials
The course materials address QualityStage essentials for DataStage XE - Version 7.x and are provided during course delivery.
Hands-On Labs
Several labs are included throughout the delivery to address and reinforce the skills discussed.
Audience
This is a basic course for system/data analysts, developers, and business analysts working on a data integration project.
This course provides the fundamental QualityStage product and methodology concepts for individuals who assess, plan, and develop data integration projects.
Prerequisites
You should:
- be familiar with Windows, the operating system (OS) running QualityStage Server, and a text editor
- have basic knowledge of Client/Server concepts and strong technical aptitude
- be comfortable working in the Windows environment and using Windows applications
Skills taught
Identify and describe data quality issues and methods
Apply the QualityStage application development process
Build QualityStage jobs and applications
- build and run data Investigation stages to uncover data values and meanings, field relationships, and business rules
- align data to a common format using QualityStage functions
- build standardize stages for conditioning US name, address, and area data
- add rule-set overrides (classification, unhandled or input text, and unhandled or input patterns)
Describe the QualityStage matching concepts (probabilistic record linkage theory)
- Build and modify a basic match stage and custom match extract file
Describe data survivorship concepts and methods
- Build a basic survive stage
Review and interpret results
Course outline
- Data quality
- Introduction to QualityStage
- Development basics
- Investigation
- Data preparation
- Standardize
- Rule set overrides
- Matching
- Survivorship
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