February 23, 2004 DataFlux Corporation, a leading provider of data management solutions that increase the consistency, accuracy and reliability of enterprise data assets, announced the general availability of DataFlux Version 6.1 technology. The new release of DataFlux software further enhances the company’s data profiling capabilities, extending the ability to verify that an organization’s information meets established data standards and business rules.
Version 6.1 contains a number of enhancements designed to help users better control their data management process. It also introduces an improved standalone application that allows business users to view possible duplicate records and establish rules to eliminate or consolidate records during the data integration process. In addition, dfPower Architect, DataFlux’s workflow designer, has been extended to permit the incorporation of external applications or scripts.
“DataFlux has traditionally provided a wide range of data management features for the business user,” said Robert Lerner, senior analyst with Current Analysis. “With Version 6.1, DataFlux now adds a number of new user-focused features that give both business and IT staff the ability to analyze, cleanse, integrate and enhance mission-critical data from the same application.”
New features available with Version 6.1 include:
- Automatic data validation Allows users to schedule jobs to find and flag information in databases that do not conform to established data standards and business rules. Exceptions can be moved into a new table, text file or report, complete with rule violation numbers and timestamps.
- Redundant data discovery Identifies duplicate data during the data profiling process using exact or fuzzy text comparisons derived from DataFlux’s sophisticated matching technology. Redundant data discovery indicates common and outlying values among the selected tables for quick duplicate value identification.
- Extended relationship analysis Examines relationships between data in different sources, helping users determine if orphaned records or cardinality violations exist in a table.
- Better multiplatform support Enhances dfPower Architect to allow users to create detailed data management routines on Windows, UNIX or Linux environments from the dfPower Architect workflow interface.
- Sampling capabilities Gives users the flexibility to profile an appropriate sample size from a large data set to quickly learn what types of data quality problems exist.
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