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Reltio Unveils Data Quality Confidence Indicator for Business Users


Reltio, provider of modern master data management for customer 360, has introduced its newest release, version 2018.3 of Reltio Cloud that includes that Data Quality Confidence Indicator for business users and enhancements for data connectivity and self-service to improve IT productivity.

Citing data from KPMG and Forrester Research, Reltio says that “60% of organizations say they are not very confident in their data and analytics insights” and “only 10% believe they excel in managing the quality of data and analytics.”

To address these issues, the Reltio Data Quality Confidence Indicators are continuously calculated for all profiles in Reltio Cloud and presented to the user as actionable metrics, enabling business users to have a consistent way of quantifying data quality for reliability and business value.

Reltio’s new data quality and ranking capability is also valuable for data stewards since it automatically prioritizes work by identifying data that is high in business value but low in quality so they can focus their time and efforts for the greatest business impact, increasing productivity, aligned to business value.

The new data confidence features in Reltio Cloud 2018.3 include:

  • Data Quality Confidence Indicators - A machine learning-based Data Quality IQ (DQIQ) score grades the quality of data in each profile, and a Reltio Rank highlights the importance and relevance of a profile compared to other profiles. Metrics are continuously updated and persisted as profile attributes, making them searchable and segmentable. DQIQ is being progressively rolled out to customers.
  • Customizable IQ Scores - Together with Reltio’s system-generated DQIQ score, customers can also leverage Reltio IQ, a separately licensed module, to customize their own DQIQ variants, and to create an unlimited number of IQ scores and attributes. Examples include Churn IQ, Upsell IQ, and Compliance IQ. 
  • Relevance-Based Matching - A new relevance-based matching option provides additional flexibility by associating an action to be performed based on a configurable relevance score of a match pair for continued data quality improvement.

For more information on the new release, go to Reltio.


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