Reverse Schema Translation for Database Accessibility
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Solution Overview
Problem
Users require expertise in data selection languages like SQL to select data from databases, limiting accessibility and widespread use of database applications.
Innovation Solution
The technology translates data sources into a reverse schema, allowing users to select data elements without knowledge of data selection languages or primary keys, using a user-friendly filtering system that generates a working list of unique identifiers and provides access to data elements based on user-selected filters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually enter SQL or data selection language statements to extract data, then data selection capability is achieved, but user expertise requirement increases and accessibility decreases
Solution Approach 1:
The patent introduces an intermediary layer between the user and the database system. This intermediary automatically generates and executes SQL queries based on user-friendly criteria selections, shielding users from SQL syntax complexity while maintaining data retrieval capability. The system translates high-level user intentions into low-level database commands without requiring users to learn the latter.
Solution Approach 2:
The patent creates a simplified copy or abstraction of the database schema that users can interact with. Instead of requiring users to work with actual SQL statements and complex table structures, the system presents a streamlined interface that mirrors database functionality at a higher level of abstraction, making data selection accessible to non-technical users.
2Ease of operation
If users join tables using primary keys and select attributes, then data extraction from relational databases is achieved, but familiarity with primary keys and table structures is required
Solution Approach 1:
The patent enables the system to automatically perform tasks that previously required user knowledge of database structure. The system self-generates the necessary JOIN operations, primary key matching, and attribute selection based on user criteria, eliminating the need for users to understand these complex database concepts while maintaining accurate data extraction.
Solution Approach 2:
The patent performs preliminary actions by pre-configuring and caching database schema information, table relationships, and primary key mappings. This preliminary processing allows the system to quickly resolve complex table joins and attribute selections without requiring users to understand the underlying database structure during the actual data extraction process.
Data Source
AI summary
Systems and methods for selecting data elements, such as population members, from a data source include translating the data source into a reverse schema. The reverse schema includes one or more data objects, each data object having a reverse access identifier and at least one unique identifier from the data source corresponding to the reverse access identifier. In some embodiments, access to data elements is provided using the reverse schema translation. A user may select a filter represented by a reverse access identifier in order to exclude those data elements associated with that reverse access identifier. In response, information associated with non-excluded data elements, such as population size, is provided for display.