Kurs informasjon: QualityStage V8 Essentials - SPVC

Please do not make travel arrangements for this course. After you receive confirmation that you are enrolled, you will be sent further instructions to access the course.

You will learn how to build QualityStage parallel jobs that investigate, standardize, match, and consolidate data records. You will gain hands-on experience by building an application that combines customer data from three source systems into a single master customer record. This is a self-paced online course and includes hands-on remote labs. Once your registration is confirmed, you will receive detailed access instructions via email. You will have 28 days access to this course when it is started. The lab uses dual client/server images, that will run continuously for 20 days (480 hours) after the lab is first launched.

The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day, but lab system access is allocated on a first-come, first-served basis. You will have a total of 40 hours allocated to complete all of the lab exercises, so when you are not using the system, ensure that you log out to maximize ability to use the lab system. Once you have accessed the course, instructor help is available via the course forum Monday through Friday; questions will be responded to within 24 hours.

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QualityStage training is needed for the following Information Server client groups:

• Data Analysts responsible for data quality using QualityStage
• Data Quality Architects
• Data Cleansing Developers

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Familiarity with:

• Windows
• A text editor
• Some knowledge of DataStage helpful

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• Describe data quality definition and issues
• Build QualityStage jobs to investigate data quality issues
• Build QualityStage jobs to cleanse data
• Consolidate duplicate records using QualityStage
• Create a consolidated view of business case customer records
• Use QualityStage to read and investigate non-English data
• Build QualityStage jobs to validate address data

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• Data Quality Issues
• QualityStage Architecture
• Developing with QualityStage
• Investigation
• Standardize
• Match
• Survivorship
• Special Topics - migration tool
• Globalization (NLS)
• Address Verification Stage

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