Data Integrity

Data integrity solutions greatly improve the completeness and accuracy of data from enterprise sources.

Today’s data sources are plagued by redundancies and duplications, lack of consistency and standardization, and missing or incomplete information. Data integrity solutions are designed to optimize the quality of enterprise data, to ensure a consistent, timely, and accurate view from each and every interaction point.

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Increase the Value of Information Capital

Omni-Gen™ Data Quality Edition is a unified platform for profiling, cleansing, and enriching information. It dramatically improves consistency, accuracy, and completeness, increasing information capital to yield higher business value. Organizations can improve data processing in transactional and analytical applications, enhance system migration or software integration projects, improve customer identification processes, and validate inputs in online applications.

Lack of data integrity is cause for continued concern among IT and business executives alike. An inability to control and manage data integrity, due to rising volumes and new sources, makes it difficult to successfully derive value from their enterprise information assets. As a result, organizations struggle to stay competitive, remain profitable, and meet evolving customer demands. Data integrity solutions can help them to overcome these challenges by ensuring the reliability, accuracy, and timeliness of critical information.

Broad-reaching capabilities ensure data is always “clean” and consistent.

Omni-Gen Data Quality Edition has extensive and broad-reaching data quality management capabilities:

  • An automated rules engine cleanses the data, triggering instant changes to existing data to eliminate mistakes
  • A real-time data quality firewall can be built, complete with real-time reporting and monitoring
  • Centralized management of business rules, information integrity, and data flows provides a single point of integration and management for data from external master data systems and other sources.
  • Restrictions, constraints, and other data quality rules can be defined and implemented, and then automatically applied to data values across the information landscape
  • Information can also be enriched and enhanced by appending it with relevant content gathered from external sources
  • Match and merge functionality synchronizes information across multiple data sets to promote consistency 
  • Robust data governance capabilities enable end to end remediation of data quality issues
  • Data can be profiled and analyzed to assess its quality and immediately identify and correct integrity issues

Import, cleanse, and export your personal data rapidly without IT