Automated Data Mapping Platform for Enterprise Risk Management
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Solution Overview
Problem
In large enterprise businesses, data management and validation across disparate systems and sources are inefficient due to data being stored in various locations, leading to human errors and difficulties in generating reports, understanding data connections, and validating calculation logic, which negatively impacts financial reporting.
Innovation Solution
A comprehensive platform that provides data mapping and linkage information across multiple data sources and systems, allowing users to access upstream and downstream data impacts, and includes a data research and risk management application that facilitates data validation by displaying calculation logic and transformation types, enabling efficient data research and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data analysis and validation is performed across disparate systems, then data field mapping can be completed, but human error and inaccuracies increase
Solution Approach 1:
The patent introduces an automated data mapping system that acts as an intermediary between disparate data sources and the target system. This system automatically identifies, extracts, and maps data fields across different systems without requiring manual intervention, thereby eliminating human error while maintaining the ability to handle complex data transformations between heterogeneous sources
Solution Approach 2:
The patent replaces the manual mechanical process of data field mapping with an automated computational system. The system uses algorithms and software agents to automatically discover data field relationships, perform mapping transformations, and validate data accuracy, substituting human manual analysis with automated mechanical processes that are more reliable and scalable
2Productivity
If data is stored in various locations across multiple systems, then data source flexibility is maintained, but data research and validation become time-consuming
Solution Approach 1:
The patent creates a universal data mapping platform that can interface with multiple different types of data sources and systems simultaneously. This universal system performs multiple functions including data discovery, field mapping, transformation, and validation across heterogeneous sources, enabling efficient data research without requiring separate manual processes for each system
Solution Approach 2:
The automated mapping system serves as an intermediary layer between the complex disparate data systems and the users needing data validation. This intermediary automatically manages the complexity of navigating multiple data sources, performing searches, and validating data across systems, thereby improving productivity without exposing users to the underlying system complexity
3Ease of operation
If data fields have different labels in different data sources, then data source independence is preserved, but data analysis and searching become problematic
Solution Approach 1:
The patent replaces manual data field interpretation with automated computational analysis. The system uses algorithms to automatically analyze data field properties, infer relationships between fields with different labels across sources, and perform semantic matching. This automated approach preserves data source independence while preventing loss of data field meaning through systematic analysis
Solution Approach 2:
The patent transforms data field identification from relying on consistent labels to using multiple parameters for field identification and matching. The system considers data type, format, relationships to other fields, and contextual information as parameters for identifying equivalent fields across different sources, even when labels differ, thereby maintaining data source independence while enabling accurate analysis
Data Source
AI summary
Systems, apparatus, and computer program products provide for a comprehensive platform in which users can gain access to data mapping and linkage information associated with multiple data sources, data systems, databases within the systems and the like. As such, the platform provides for time-efficient and reliable data management and research which aids the user in comprehending the connections between data from different data sources and included within different data systems, and the downstream impact (i.e., the impact of the data on other data fields) and upstream data source(s) (i.e., the secondary data fields used to calculate the data filed) of such data.