SQL Metric Calculation Chaining for Database Analysis
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Solution Overview
Problem
Existing database systems are inefficient due to limitations in using metric results within Structured Query Language (SQL) statements, which often require users to develop multiple sets of SQL statements to achieve desired insights, leading to time-consuming and inefficient reporting and analysis.
Innovation Solution
A method that allows users to utilize multiple metric calculations as sources or drivers within SQL statements, enabling complex rule chaining and dynamic processing of these calculations to provide combined results that can be used as inputs or drivers for further SQL processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users develop multiple different sets of SQL statements to account for metric results, then the ability to derive insights from database metrics is improved, but the time consumption and operational efficiency deteriorate
Solution Approach 1:
The patent combines multiple SQL statements and their associated metric calculations into a single integrated SQL statement. The system identifies metric calculations within the SQL statement, processes them against the database, and allows the results to be used as sources for target rules within the same statement, eliminating the need for multiple separate SQL iterations and reducing time consumption while maintaining full insight derivation capability
Solution Approach 2:
The patent enables continuous processing where metric calculation results flow directly into target rule processing within the same SQL statement execution. This creates a continuous workflow where the output of metric calculations immediately becomes the input for rule evaluation, eliminating interruptions and repeated SQL statement submissions, thereby reducing time loss while maintaining comprehensive analysis capability
2Loss of information
If users develop multiple different sets of SQL statements to account for metric results, then the ability to derive insights from database metrics is improved, but the operational efficiency deteriorates
Solution Approach 1:
The patent merges multiple SQL statements into one integrated statement that can process metric calculations and apply target rules in a single execution. This consolidation maintains the full capability to derive insights from database metrics while significantly improving operational efficiency by eliminating the need to submit and process multiple separate SQL statements
Solution Approach 2:
The patent creates a universal SQL statement structure that can handle both metric calculations and target rule processing within a single framework. This multi-functional approach allows the same SQL statement to perform multiple operations (metric extraction, calculation, and rule application) that previously required separate statements, thereby improving productivity without sacrificing analytical depth
3Ease of operation
If metric results cannot be used as source or driver to complex rules in SQL statements, then the SQL processing simplicity is maintained, but the flexibility and adaptability of the system deteriorates
Solution Approach 1:
The patent introduces an intermediary processing layer within the SQL statement execution that handles metric calculations and makes their results available as sources for target rules. This intermediary mechanism maintains the simplicity of SQL processing for users while enabling flexible adaptation by allowing metric results to drive complex rules, effectively bridging the gap between simple processing and high adaptability
Data Source
AI summary
Techniques for using database metric results are provided. Structure Query Language (SQL) statements are parsed for multiple metric calculations. Each metric calculation is dynamically processed against a database to obtain combined results. The combined results are fed to remaining portions of the SQL statements as a source for or a driver to the remaining portions of the SQL statements.