Data Maintenance
User Roles
| Activity | ST | DS | DM | AD |
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| Create ad hoc queries |
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| Work with Data Quality Reporting |
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| Run Data Maintenance jobs |
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| Configure match rules |
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| Create rule expressions |
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Key Concepts
Veeva Network provides a number of ways to ensure and maintain the best possible customer master data
A customer instance of Veeva Network that contains both Veeva OpenData data (if subscribed) as well as customer-owned records and data..
Network Reporting enables you to quickly and easily create queries Controls (similar to SQL queries) for using available keywords, tables, fields, and operators to analyze data in a Network instance. to analyze data in your customer instance. It can help to pinpoint quality issues (for example, entities without active addresses); perform task reporting and management activities, such as identifying change request resolution rates by data steward; or analyze match logs to determine the effectiveness of match rules A definition that determines which fields in a record are a possible match and when a record comparison is considered a suspect match. See features and feature sets.. Data Quality Reports A suite of tests that quantify and summarize potential issues in customer master data. builds on the reporting functionality by simplifying the process of generating, presenting, and consuming reports designed to highlight quality issues. Both methods of reporting are extendible for optimal flexibility.
Data maintenance User directed automated jobs that improve data quality by targeting specific data quality issues like sub-object inactivation and data deduplication detection. jobs in Network enable you to inactivate sub objects This term is no longer used. It has been replaced by sub-object. from HCOs or HCPs that have already been deactivated, or to identify duplicate records in your customer master data. Rule expressions A user-defined rule applied to Network data loads which can be used to apply transformations to the data during the load. enable you to transform data on load, while match rule configuration can help you further tweak your data quality before it becomes an issue.