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How Business Workflow Lineage Accelerates Root-Cause Analysis of Data Quality Exceptions

Reading time: 3 min   |  By Sonia Chopra   |  Published in Articles,

As firms continue to produce mass amounts of data, data quality errors are expected to occur. However, the success of a business depends on how effectively these issues are handled, resolved, and prevented. If firms operate in silos or continue to use static data management tools, achieving continuous end-to-end data quality becomes difficult. As a result, operational efficiency, regulatory compliance, and business decision-making is likely to suffer. Implementing the right data quality monitoring tool is the only solution to reducing the resources and time it takes to perform root-cause analysis of data quality exceptions.

Challenges with Current Data Quality Tools

Current siloed exception reporting makes root-cause analysis difficult and costly. Firms are constantly performing duplicate investigations and experiencing false positives. This increases operational costs and resource wastage, as multiple resources are utilized to investigate the same issues.

Additionally, today’s data quality and governance tools claim to provide “data lineage”. In reality, they only provide metadata lineage, however. These tools do not include any transactional values, and are insufficient when answering and resolving data quality questions.

PeerNova’s Cuneiform Platform
Business Workflow Lineage for Faster Root-Cause Analysis of Data Quality Exceptions

Cuneiform® is a zero-code platform that provides data quality monitoring, business value impact, and exception resolution across internal and external data sources.

Through the Business Workflow Lineage™ feature, the solution accelerates root-cause analysis of data quality issues. Cuneiform provides users with traceability and a complete data quality view across systems, applications, and workflows. It enables users to track, report, and fix exceptions across their transactional workflows in real-time. Exceptions are quickly identified without any duplicate investigative effort.

Additionally, no manual effort is needed to collate multiple exception reports. PeerNova’s data quality monitoring tool provides relationship-based and series lineages that lend business context to transactional workflows. For every transaction or business event in a workflow, Cuneiform provides a complete lineage from inception to completion to easily locate, trace, and resolve any and all exceptions in real time.

Additionally, firms can use Cuneiform to prioritize their data quality exceptions based on their business impact to resolve the most critical issues. By discovering the impact of data quality issues across relevant business metrics in real time, firms can prioritize fixes that may result in credit risk, regulatory fines, and more.

By implementing the Cuneiform Platform, firms can accelerate their root-cause analysis of data quality exceptions and ensure continuous end-to-end data quality monitoring. If you are ready to see the solution in action, request a demo today!


By Sonia Chopra

Sonia Chopra is PeerNova's Product Marketing Manager for the Valuation Risk product line. She has nearly a decade of marketing experience and has been with PeerNova for eight years. She specializes in crafting content and campaigns that address the complexities of product and valuation control, such as market volatility, asset pricing discrepancies, and regulatory compliance issues. Her ability to articulate the intricacies of these challenges, enables her to develop highly effective product marketing strategies that meet the evolving needs of the industry.

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