September 2001
Beginner
544 pages
17h 43m
English
Content preview from DATA WAREHOUSING FUNDAMENTALS: A Comprehensive Guide for IT Professionals
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13.8. EXERCISES
Match the columns:
domain integrity
data aging
entity integrity
data consumer
poor quality data
data consistency expert
error discovery
data pollution source
dummy values
data quality benefit
detect inconsistencies
better customer service
synchronize all data
allowable values
used to pass edits
uses warehouse data
heterogeneous systems integration
lost business opportunities
prevents duplicate key values
decay of field values
Assume that you are the data quality expert on the data warehouse project team for a large financial institution with many legacy systems dating back to the 1970s. Review the types of data quality problems you are likely to have and make suggestions on how to deal with those.
Discuss the common sources of data pollution and provide examples.
You are responsible for the selection of data cleansing tools for your data warehouse environment. How will you define the criteria for selection? Prepare a checklist for evaluation and selection of these tools.
As a data warehouse consultant, a large bank with statewide branches has hired you to help the company set up a data quality initiative. List your major considerations. Produce an outline for a document describing the initiative, the policies, and the procedures.
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