Customer information is collected, stored, and maintained in many different files, systems, and databases within a typical organization. This data is continually transferred among systems, transformed for a variety of different purposes, touched again and again by human and machine, often leaving a collection of redundant, non-standardized, incorrect, incomplete, and conflicting versions of names and addresses spread throughout the organization.
These systems may be independent, and additions and changes to customer data are often not synchronized among systems. A customer may appear in more than one system by purchasing different products and services. For applications that use data from more than one system (e.g., Call Center, CRM, SCM, Data Warehouse), it may appear that
the enterprise has more unique customers than it actually does, and
the relationships among customers may not be well-defined. This lack
of accurate data can result in several issues, including redundant mailings, ineffective call center operations, and inaccurate cross-sell and trend analysis.
i/Lytics Data Quality and Data Linking are designed to accept such data and apply parsing, standardizing, and linking rules to draw customer intelligence from the disparate sources.
This class is for anyone who is:
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A current user of i/Lytics Data Quality and/or Data Linking who would like to enhance their skills and maximize their investment
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Interested in gaining detailed knowledge and hands-on application of i/Lytics Data Quality or Data Linking tools
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Considering or evaluating a Data Quality or Linking solution
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Interested in learning about Innovative’s best practices for achieving high customer Data Quality
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Interested in learning more about creating and maintaining a customer-centric database
