Unified Database Translation Using Key-Based Entity Aggregation
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Solution Overview
Problem
Businesses face challenges in organizing disparate data from various sources into a single, unified database due to differing formats and techniques, making manual conversion impractical and time-consuming.
Innovation Solution
An automated system that receives data from multiple sources, parses and configures it into cells, identifies primary and foreign keys, aggregates entities with matching keys, and transmits them to a destination data store while excluding duplicates or outdated versions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual conversion and organization of data from disparate sources is performed, then data can be organized into a unified database, but the process becomes time-consuming and impractical due to sheer volume and complexity
Solution Approach 1:
The system enables self-service data integration by automatically detecting data sources, parsing various formats, identifying entities and relationships, and transforming data into a unified schema without requiring manual intervention for each data conversion task
Solution Approach 2:
The system dynamically adjusts parsing parameters, entity recognition thresholds, and relationship detection criteria based on the characteristics of each data source, allowing adaptive processing that maintains accuracy while optimizing processing speed for different data types and volumes
2Productivity
If automated parsing and configuration is applied to handle large volumes of disparate data, then processing speed and productivity improve, but system complexity increases
Solution Approach 1:
The system segments the complex data integration process into distinct modular components: data source detection module, format parsing module, entity recognition module, relationship extraction module, and schema transformation module. Each module handles a specific aspect of the process independently, improving productivity while managing complexity through functional decomposition
Solution Approach 2:
The system implements universal data structures and standardized schemas that can accommodate multiple data sources and formats. The entity-relationship model serves as a universal framework that can represent diverse data types from different sources, reducing the need for source-specific processing logic and simplifying the overall system architecture
3Quantity of substance
If data from multiple disparate sources with varied formats and schemas is integrated into a single unified database, then data completeness and analytical capability improve, but the difficulty and time required for organization increase
Solution Approach 1:
The system introduces an intermediary layer consisting of standardized data schemas and entity relationship models that mediate between diverse source data formats and the target unified database. This intermediary layer translates various source formats into a common structure, enabling data completeness while managing integration complexity through standardization
Solution Approach 2:
The system performs preliminary actions by pre-defining data schemas, entity types, and relationship structures before actual data integration occurs. This advance preparation of the target database structure and transformation rules simplifies the integration process and reduces the complexity of handling disparate source data
Data Source
AI summary
The disclosed systems and methods can include receiving data files from various data sources to create a unified database. An appropriate configuration for the data files is determined. Each data file is parsed into cells and associated with an entity. The appropriate configuration is applied to the cells and the cells containing primary keys and foreign keys are identified. The related entities are linked via the foreign keys. The entities are aggregated based on the primary keys. Entities that are duplicates to the entities stored in the destination database are excluded from the aggregate and the aggregate is transmitted to the destination database.