Enterprise Object Model for Data Integration
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Solution Overview
Problem
Pharmaceutical companies face significant challenges in generating and approving annual product quality reviews due to the disparate and ill-communicating data sources, requiring extensive manual effort and consuming valuable resources.
Innovation Solution
A system and method that ingest raw data from multiple systems of record, map it to standardized enterprise object models, and provide integrated data for automated report generation, utilizing a tech fabric enterprise solution with modules like APIs, data transformation, and domain models to streamline data integration and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data aggregation from multiple systems is performed, then data accuracy and completeness can be ensured, but time consumption and resource expenditure increase significantly
Solution Approach 1:
The patent replaces manual mechanical data aggregation processes with an automated computer system that uses scripts to extract, transform, and load data from multiple systems of record. The system automatically maps data from disparate sources to a unified enterprise object model, eliminating the need for manual collection and processing of data while maintaining accuracy through structured validation protocols.
Solution Approach 2:
The system enables self-service data integration where the automated framework independently performs data extraction, transformation, and consolidation without requiring continuous manual intervention. The framework self-manages the complex coordination between multiple systems of record, automatically handling data mapping and integration based on predefined configurations.
2Adaptability or versatility
If data is aggregated from multiple disparate systems, then comprehensive review coverage is achieved, but system complexity and integration difficulty increase
Solution Approach 1:
The patent implements a universal enterprise object model framework that serves as a common data structure for integrating multiple systems of record. This single unified model accommodates data from diverse sources including but not limited to manufacturing execution systems, ERP systems, quality management systems, and electronic batch records, allowing one framework to handle multiple integration scenarios without requiring separate specialized systems for each data source.
Solution Approach 2:
The system introduces an intermediary data transformation layer that acts as a mediator between disparate systems of record and the final integrated view. This intermediate layer handles the complexity of data mapping, format conversion, and normalization, shielding the upper layers from the underlying system complexities while maintaining comprehensive review coverage across all data sources.
3Reliability
If extensive manual review and approval processes are implemented, then report accuracy and compliance are ensured, but processing time and resource consumption increase
Solution Approach 1:
The system enables continuous automated data aggregation and report generation without interruption, operating continuously to collect and process data from all systems of record. This continuous operation eliminates the batch processing limitations of manual review cycles, maintaining steady progress on report generation while ensuring accuracy through ongoing validation protocols.
Solution Approach 2:
The patent implements feedback mechanisms where the system automatically validates data quality, checks for completeness, and identifies anomalies in the aggregated data. This automated feedback loop continuously monitors report generation processes and triggers corrective actions when issues are detected, ensuring report accuracy while operating at automated speed without requiring manual intervention for each validation step.
Data Source
AI summary
A method of accessing data from disparate data sources at a data access layer, the method comprising: receiving a request to ingest raw data from a plurality of systems of record; ingesting raw data from the plurality of systems of record based on the received request to ingest raw data; mapping the ingested raw data to a plurality of unpopulated enterprise object models to standardize the ingested raw data and to populate the enterprise object models; storing the standardized data and the plurality of populated enterprise object models; and providing the plurality of populated enterprise object models to the data access layer for accessing the standardized data.