Data Contract Enforcement for Natural Language Data Queries
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Solution Overview
Problem
Querying data across multiple heterogeneous data sources is complex due to the need for specialized knowledge and the disparity between data contract specifications and implemented code, leading to errors in enforcement.
Innovation Solution
An analysis system that enforces data contracts by using a machine learning-based language model to generate database queries from natural language questions, maps data assets, and executes queries while maintaining metadata privacy, allowing users to interact with heterogeneous data sources through a natural language interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users directly interact with heterogeneous data sources using specialized knowledge, then data access capability is improved, but operation complexity and barrier to entry increase
Solution Approach 1:
The patent introduces a natural language processing intermediary layer between users and heterogeneous data sources. This mediator translates user-friendly natural language queries into system-specific query languages, eliminating the need for users to learn multiple data source protocols while maintaining broad data access capability across different systems
Solution Approach 2:
The system creates a universal natural language interface that works across multiple heterogeneous data sources simultaneously. Instead of requiring separate interaction methods for each data source type, a single natural language processing mechanism handles queries to relational databases, file systems, cloud storage, and other diverse data sources uniformly
2Reliability
If manual code implementation is used to enforce data contracts, then enforcement capability is improved, but error rate and maintenance complexity increase
Solution Approach 1:
The patent replaces manual code-based data contract enforcement with an automated machine learning model. This AI-driven system automatically generates, validates, and enforces data contracts without human intervention, eliminating errors associated with manual coding while maintaining strong enforcement capability through intelligent constraint verification
Solution Approach 2:
The system enables self-service data contract enforcement where the machine learning model autonomously generates appropriate constraints and validation rules based on data source characteristics. The system automatically adapts to new data sources and contract requirements without requiring manual programming, reducing both error rates and maintenance overhead
Data Source
AI summary
An analysis system enforces data contracts between systems associated with entities. The analysis system identifies a data source of a provider system for processing a request to access data. The analysis system identifies a set of data contract specifications between the provider system and the consumer system. For each data contract specification, the analysis system evaluates the constraints of the data contract specification to determine whether executing the request to access data violates a constraint. A constraint may specify execution cost of a data processing request. If a constraint is violated by execution of the request, the analysis system identifies the data contracts that are violated and sends information describing violations of the one or more data contracts for display via a user interface.