Hierarchical Query Schema for Faster Versioned Data Retrieval
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Solution Overview
Problem
Existing systems face inefficiencies in querying and managing hierarchically-structured data, leading to increased processing power requirements, redundant data storage, and inaccuracies in data versioning, particularly in medical coding systems.
Innovation Solution
The implementation of hierarchically-structured data and query sets that utilize a hierarchical query schema, allowing for efficient data retrieval by reducing search space and eliminating redundant data, while incorporating revision control for accurate data versioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional flat data structures are used for storage, then data retrieval requires scanning the entire dataset, but this leads to increased processing power requirements and longer query times
Solution Approach 1:
The patent segments hierarchical data into parent-child relationships with unique identifiers, allowing the query system to divide the search space into manageable sections. Instead of scanning entire datasets, the system navigates through hierarchical segments using reference identifiers, dramatically reducing the processing power needed for data retrieval operations.
Solution Approach 2:
The patent introduces a hierarchical dimension to data storage by organizing data in parent-child relationships across multiple levels. This dimensional transformation allows the system to navigate through hierarchical paths rather than linearly scanning flat structures, enabling faster retrieval by jumping directly to relevant data sections through reference identifiers.
2Productivity
If complete hierarchical data structures are stored to enable efficient querying, then data retrieval efficiency improves, but memory requirements increase
Solution Approach 1:
The patent extracts only the essential hierarchical reference information (parent identifiers and child identifiers) needed for navigation, rather than storing complete hierarchical contexts for every data element. This extraction approach maintains efficient hierarchical querying capability while minimizing the quantity of stored data, thereby reducing memory requirements.
Solution Approach 2:
The patent uses lightweight reference copies (identifiers) to represent hierarchical relationships instead of duplicating entire hierarchical structures. Each data element stores references to its parent and children rather than maintaining full copies of hierarchical contexts, enabling efficient navigation with minimal memory consumption.
3Reliability
If data versioning is implemented to track changes, then data accuracy improves, but system complexity increases due to managing multiple versions
Solution Approach 1:
The patent incorporates version tracking as a preliminary attribute in the hierarchical data structure, with each node containing version information from the outset. This preliminary integration of versioning into the core data structure eliminates the need for separate version management systems, reducing overall system complexity while maintaining data accuracy.
Solution Approach 2:
The patent nests version information within the hierarchical data structure itself, embedding version attributes inside individual data nodes rather than maintaining external version control mechanisms. This nesting approach allows version tracking to be an intrinsic part of the data structure, simplifying the overall system architecture while ensuring data accuracy.
4Speed
If redundant data is stored to facilitate quick access, then data access speed improves, but data normalization and storage efficiency deteriorate
Solution Approach 1:
The patent creates lightweight reference copies (identifiers) that point to hierarchical data elements rather than duplicating entire data records. These reference copies enable quick access through hierarchical navigation while maintaining data normalization by storing only essential reference information rather than redundant data copies.
Solution Approach 2:
The patent segments data access into hierarchical steps using reference identifiers, allowing the system to quickly navigate to specific data sections without loading entire redundant datasets. This segmented approach maintains data normalization by storing minimal reference information while achieving fast access through efficient hierarchical traversal.
Data Source
AI summary
A method for querying hierarchical data from a database includes receiving a request to generate a first query set data object associated with a query set including a first query and a second query. The first query is first query type and the second query is a second query type. The method includes generating the first query set data object which is structured according to a hierarchical query schema. The method includes generating a first query data object associated with the first query. The method includes generating a second query data object associated with the second query. The method includes executing the first query and the second query of the query set on the database to select matching hierarchical data. The method includes selecting a datasheet from a second database of the provider computing system, the datasheet including outmoded hierarchical data and replacing the outmoded hierarchical data of the datasheet.