Query Broker System for Enterprise Data Accessibility
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Solution Overview
Problem
Current data systems lack the capability to facilitate consistent data queries across an enterprise, leading to inefficiencies and bottlenecks as non-analysts rely on analysts for data retrieval, resulting in long lead times and redundant work due to the requirement of technical knowledge in database queries.
Innovation Solution
A query broker system that allows users to configure and execute structured data queries without specialized training by generating executable queries based on user input, enabling non-analysts to access and retrieve data from a database system, reducing the need for analyst assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a central repository of pre-configured queries is provided, then data accessibility is improved, but the system becomes unusable by untrained employees due to requiring knowledge of databases and query language
Solution Approach 1:
The patent introduces a query broker as an intermediary layer between users and the database system. The query broker receives natural language queries from users, translates them into executable database queries, and returns results. This mediator eliminates the need for users to directly interact with complex database interfaces while maintaining full data accessibility capabilities.
Solution Approach 2:
The patent replaces the mechanical interaction of manual query writing and database interface navigation with an automated natural language processing system. Instead of requiring users to mechanically construct SQL or database-specific queries, the system automatically generates executable queries from human-readable natural language inputs.
2Reliability
If non-analysts rely on analysts for data retrieval, then data consistency is maintained, but efficiency is reduced due to bottlenecks and long lead times
Solution Approach 1:
The patent enables self-service data retrieval by allowing any user to independently execute queries through natural language interfaces. The query broker automatically handles query translation, execution, and result delivery without requiring analyst intervention. This self-service capability maintains data consistency through standardized query processing while dramatically improving retrieval efficiency and eliminating bottlenecks.
3Measurement precision
If trained analysts write and rewrite queries to pull similar data, then data accuracy is improved, but productivity is reduced due to redundant work
Solution Approach 1:
The patent implements preliminary action by pre-compiling and caching frequently executed queries in the query broker. When a user submits a natural language query, the system checks against cached results and executes only when necessary. This preliminary preparation of query structures and results significantly reduces redundant work while maintaining data accuracy through consistent query execution.
Data Source
AI summary
In some embodiments, in connection with a user input of a user, a set of selective parameters to be configured by the user for a structured data query may be determined. As an example, the set of selective parameters may be a first set of selective parameters for the structured data query in response to the set of permissions being a first set of permissions. As another example, the set of selective parameters may be a second set of selective parameters different from the first set of selective parameters in response to the set of permissions being a second set of permissions. One or more input fields for configuring one or more selective parameters of the set of selective parameters may be generated for display, and an executable data query may be generated based on configuration information (related to the selective parameters) that is obtained via the input fields.