Two-Dimensional Grid for Data Validation Rule Specification

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Solution Overview

Problem

Existing data validation systems lack an efficient and intuitive method for specifying and applying validation rules to datasets, leading to potential delays and resource inefficiencies in ensuring data quality, particularly in large-scale applications where data quality can significantly impact application performance.

Innovation Solution

A computing system that utilizes a user interface to render a two-dimensional grid for specifying and applying validation rules, allowing users to select and apply rules to dataset fields with immediate feedback, enabling quick validation and modification of rules without requiring full dataset processing, and includes features for custom and pre-defined rules, as well as feedback indicators for rule compliance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional data validation systems process the entire dataset to apply validation rules, then data quality can be ensured, but time consumption and resource usage increase significantly

Engineering Contradiction:
Improvedata qualityVSAvoidvalidation time
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies partial action by processing only a sample subset of the dataset rather than the entire dataset. The system selects a representative sample from different portions of the dataset and applies validation rules to this smaller subset, thereby significantly reducing validation time while still providing reliable indicators of overall data quality through the sample results

Inventive Principle:
Principle #16Partial or excessive action

Solution Approach 2:

The system performs preliminary action by first identifying and selecting a representative sample subset before applying validation rules. This preliminary sampling step allows the system to prepare an optimized validation approach that reduces subsequent processing time while maintaining data quality assurance

Inventive Principle:
Principle #10Preliminary action

2Reliability

If validation rules are specified through complex programming interfaces, then validation accuracy can be maintained, but ease of use deteriorates

Engineering Contradiction:
Improvevalidation accuracyVSAvoidrule specification ease
Core Design Contradiction:
ReliabilityVSEase of operation

Solution Approach 1:

The patent implements feedback by providing real-time visual feedback in the grid interface as users specify validation rules. The system displays validation results, data quality metrics, and rule application status directly in the grid cells, allowing users to immediately see the impact of their rule specifications and adjust accordingly, thereby simplifying the rule specification process while maintaining accuracy

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system applies self-service by automatically selecting representative sample subsets and applying validation rules based on user-defined criteria without requiring complex programming. The automated sample selection and rule application processes enable non-programmers to effectively specify and execute validation rules through the intuitive grid interface

Inventive Principle:
Principle #25Self-service

3Measurement precision

If the system processes large datasets to provide comprehensive validation results, then measurement precision improves, but productivity decreases

Engineering Contradiction:
Improvevalidation result precisionVSAvoidvalidation throughput
Core Design Contradiction:
Measurement precisionVSProductivity

Solution Approach 1:

The patent applies segmentation by dividing the large dataset into multiple segments and selecting representative samples from different segments. The grid interface organizes data into rows and columns representing different segments, allowing the system to process multiple segments in parallel or selectively, thereby maintaining measurement precision through comprehensive coverage while improving productivity through efficient resource utilization

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP2909750B1Specifying and applying rules to data
Publication Date: 2019.12.04 AB INITIO TECHNOLOGY LLC
  • EP2909750B1 patent drawingFigure 1
  • EP2909750B1 patent drawingFigure 2
  • EP2909750B1 patent drawingFigure 3

AI summary

Validation rules validate data included in fields of elements of a dataset. Cells (224) are rendered in a two-dimensional grid (225) that includes: one or more subsets of cells extending in a direction along a first axis (228), each associated with a respective field (218), and multiple subsets of cells extending in a direction along a second axis (226), one or more of the subsets associated with a respective validation rule (234). Validation rules are applied to at least one element based on user input received from at least some cells. Some cells, associated with a field and a validation rule, can each include: an input element for receiving input determining whether or not the associated validation rule is applied to the associated field, and/or an indicator for indicating feedback associated with a validation result based on applying the associated validation rule to data included in the associated field.