Automated Data Exporter Generator for Heterogeneous Source Consolidation
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Solution Overview
Problem
The challenge lies in efficiently consolidating vast volumes of heterogeneous demographic data from various incompatible data sources into a common repository, which is essential for applying advanced information technology to improve medical service efficiency and reduce costs, but is often overwhelmed by the complexity and volume of data.
Innovation Solution
A data exporter/importer system is developed, comprising a data exporter generator and importer, which automatically generates data exporters for heterogeneous data sources, validates and transforms data into a unified format, and imports it into a destination data repository, leveraging knowledge of the destination repository to ensure organized and modeled data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual or piecewise data consolidation efforts are used, then data can be processed and consolidated, but the process becomes overwhelming and inefficient when facing massive volumes of data from multiple heterogeneous sources
Solution Approach 1:
The system segments the data consolidation process by generating separate data exporter components for each heterogeneous data source. Each exporter is specialized for its specific source type (e.g., database exporter, file exporter), allowing independent processing and management of different data formats without overwhelming the entire system.
Solution Approach 2:
The system implements a universal data importer that can receive and process data from multiple different data sources through their respective exporters. The importer serves multiple functions by accommodating various data formats and source types while maintaining a single unified interface for data consolidation into the destination repository.
2Productivity
If data is exported and imported through automated generators, then data consolidation speed increases, but the system complexity increases due to need for data schemas and generator components
Solution Approach 1:
The system performs preliminary actions by generating data exporters in advance based on data schemas before actual data consolidation occurs. These pre-generated exporters are ready to immediately process data from their respective sources when needed, eliminating the need for manual configuration during data consolidation operations.
Solution Approach 2:
The system creates copies of data structure definitions through data schemas that describe the format and organization of data. These schemas serve as templates that generate corresponding exporter components, allowing the system to replicate and adapt data handling logic for different sources without rewriting code from scratch.
3Adaptability or versatility
If heterogeneous data from multiple sources is consolidated into a unified repository, then data accessibility and IT application improve, but data transformation and validation complexity increases
Solution Approach 1:
The system introduces data schemas as intermediary representations that define the expected structure and format of data in the destination repository. These schemas act as mediators between the various heterogeneous data sources and the unified repository, enabling automatic transformation and validation by comparing source data against the schema definitions.
Data Source
AI summary
Embodiments of the present invention provide methods and systems for exporting data from a number of data sources using a number of corresponding data exporters, and importing the exported data into a destination data repository using a data importer. In various embodiments, the data exporters may be automatically generated using a data exporter generator adapted to generate the data exporters in view of data schemas of the data sources.