This course teaches how to build Quality Stage parallel jobs that investigate, standardize, match, and consolidate data records. Students will gain experience by building an application that combines customer data from three source systems into a single master customer record.
Participants should have:
? Familiarity with the Windows operating system
? Familiarity with a text editor
Helpful, but not required, would be some understanding of elementary statistics principles such as weighted averages and probability.
?Describe QualityStage clients and their functions
?Build and run DataStage/QualityStage jobs, review results
?Build Investigate jobs
?Use Character Discrete, Concatenate, and Word Investigations to analyze data fields
?Describe the Standardize stage
Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace.
This course will step you through the QualityStage data cleansing process. You will transform an unstructured data source into a format suitable for loading into an existing data target. You will cleanse the source data by building a customer rule set that you create and use that rule set to standardize the data. You will next build a reference match to relate the cleansed source data to the existing target data.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course
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