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You face five different data preparation scenarios. Match a data quality issue to each scenario. Each data quality issue can be used only once. #

You face five different data preparation scenarios. Match a data quality issue to each scenario. Each data quality issue can be used only
once.
#
Scenario
Data Quality Issue
Grace received a data set that had a column titled ClientInfo. Each record
in that field contained a client's mailing address.
The data in the Sales column are the dollar amounts of the sale
transactions. However, Quinn noted that the data type was classified as
alphanumeric characters or text data.
Upon inspection of data transferred from the payroll system to a data
warehouse, Molly noticed that employee payroll records only included
employees with last names beginning A through S.
Barnes received a table of data from the IT group. One of the columns
contains both customer name data and payment term data.
Devon extracted data from the company's shipping department log. In
addition to shipment data, the log also contains summary statistics such
as the total quantity shipped. Upon inspection of the extracted data,
Devon notes that the total quantity shipped for the extracted data does
not match the total quantity shipped number in the log.
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