18495445. DECISION IMPLEMENTATION WITH INTEGRATED DATA QUALITY MONITORING simplified abstract (Capital One Services, LLC)

DECISION IMPLEMENTATION WITH INTEGRATED DATA QUALITY MONITORING

Organization Name

Capital One Services, LLC

Inventor(s)

Thomas Grimes of Arlington VA (US)

Kenneth Wydler of Arlington VA (US)

DECISION IMPLEMENTATION WITH INTEGRATED DATA QUALITY MONITORING - A simplified explanation of the abstract

This abstract first appeared for US patent application 18495445 titled 'DECISION IMPLEMENTATION WITH INTEGRATED DATA QUALITY MONITORING

Simplified Explanation

The patent application describes a computer-implemented method for flagging data quality errors by applying rules to upstream data and executing downstream tasks based on the identified errors.

• Upstream data is received from multiple sources.
• A downstream task is identified for execution.
• Rules are applied to the upstream data.
• Outputs are generated for each rule applied, with each output associated with a specific rule.
• A tagged population is identified based on the outputs.
• Errors are detected if any output does not meet the corresponding rule threshold.
• Downstream execution is activated for the tagged population after updating the rule threshold or overriding an error.

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1. 1. 1. Potential Applications

• Data quality management in various industries such as finance, healthcare, and e-commerce.
• Automated error detection and correction in large datasets.

1. 1. 1. Problems Solved

• Efficient identification and handling of data quality errors.
• Streamlining downstream tasks based on identified errors.

1. 1. 1. Benefits

• Improved data accuracy and reliability.
• Increased efficiency in error detection and correction processes.
• Automation of data quality management tasks.

Original Abstract Submitted

Computer-implemented methods and systems include downstream execution for individual rule-based flagging of upstream data quality errors by receiving upstream data from a plurality of sources, identifying a downstream task to be executed, applying a plurality of rules to the upstream data, generating a plurality of outputs including at least one output for each of the plurality of rules applied to the upstream data, each of the plurality of outputs being associated with a corresponding rule of the plurality of rules, identifying a tagged population based on the plurality of outputs, determining that at least one of the plurality of outputs does not meet a corresponding rule threshold, and activating the downstream execution for the tagged population after at least one of (i) updating the corresponding rule threshold or (ii) overriding an error.