Denormalized Privacy Table for Cross-Entity Query Optimization
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Solution Overview
Problem
Complex computing environments managing data for multiple entities face challenges in consistently and efficiently handling diverse privacy and data governance requirements across disparate database objects, leading to error-prone and cumbersome solutions.
Innovation Solution
An API is provided that returns user records matching specific privacy criteria by denormalizing related privacy values into a database table, using a state machine pattern for initial population and map resolving logic to account for privacy values and user data, enabling dynamic structured queries for real-time responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If privacy values are stored in disparate database tables for multiple entities, then data governance requirements can be maintained for each entity, but query complexity and error rates increase significantly
Solution Approach 1:
The patent merges privacy values from multiple disparate database tables into a single denormalized table that consolidates privacy information for all entities. This consolidation eliminates the need to query multiple separate tables, reducing query complexity while maintaining complete privacy evaluation capabilities across all entities.
Solution Approach 2:
The patent introduces a new dimensional organization by denormalizing privacy data into a table structure that adds an entity type dimension. Instead of separate tables for contacts, accounts, and leads, the solution creates a unified table with an entity_type column that distinguishes between different entity kinds, enabling simplified queries while preserving entity-specific privacy requirements.
2Adaptability or versatility
If separate database tables are used for different entity types (contacts, accounts, leads), then entity-specific privacy requirements can be maintained, but real-time privacy query performance deteriorates
Solution Approach 1:
The patent combines privacy data from separate entity tables into a single denormalized table that pre-joins privacy values with entity identifiers and types. This merging eliminates the need for complex multi-table joins during query execution, enabling real-time privacy evaluation while maintaining entity-specific privacy requirements through the entity_type field.
Solution Approach 2:
The patent performs preliminary denormalization of privacy data during data insertion or update operations, rather than during query operations. By pre-computing and storing the joined privacy information in the denormalized table, the system prepares the data in advance for rapid retrieval, improving query response time while preserving entity-specific privacy handling capabilities.
3Loss of information
If denormalized privacy table is populated from multiple sources, then complete privacy data is captured, but data population complexity and potential errors increase
Solution Approach 1:
The patent implements a feedback mechanism using triggers that automatically detect when privacy values change in the source tables and initiate corresponding updates in the denormalized privacy table. This feedback loop ensures complete privacy data capture while eliminating manual population complexity and reducing errors by automating the data synchronization process.
Solution Approach 2:
The denormalized privacy table populates and maintains itself through automated triggers and constraints that respond to changes in source tables. The system serves its own data population needs through self-triggering mechanisms, eliminating the need for complex external population processes and reducing the potential for human error while ensuring complete privacy data capture.
Data Source
AI summary
At least one database table of denormalized values corresponding to selected values of field properties in records across multiple disparate tables of the database environment is maintained. A structured query is received through a structured query language application program interface (API). The structured query to request a listing of records across the multiple disparate tables of the database environment. The database table is searched for indications corresponding to records across the multiple disparate tables of the database environment corresponding to the selected values indicating communication with a specified party. A listing of records from across the multiple disparate tables that satisfy the selected values is returned through the structured query language API.