Data Quality, part of SAP Data Services, is a powerful tool for cleansing and matching customers, businesses, postal addresses, and much more. However, the wide range of options and capabilities can be intimidating for new users. In this post, we will discuss configuration of the address cleanse and data cleanse transforms.
Configuring the AddressCleanse Transform
The cleanse transform editor is very similar to that of the query transform, with the input schema in the upper left, the output schema in the upper right, and a set of tabs below. In a cleanse, however, we only have three tabs: Input, Options, and Output.
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About Bruce Labbate
Bruce Labbate is a business intelligence consultant specializing in data warehousing, data quality, and ETL development. Bruce delivers customized SAP Data Services solutions for customers across all industries. With Decision First Technologies, Bruce utilizes Data Integrator, Data Quality, Information Design Tool, and a variety of database technologies, including SQL Server, DB2, Oracle, Netezza, and HANA.