Automated Database Schema Generation via Variable Correlation
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Solution Overview
Problem
Current database management systems require significant manual effort and human intervention for design, maintenance, and error resolution, leading to high costs and complexity, especially with growing database volumes and potential issues like improper primary key assignment and data normalization problems.
Innovation Solution
A database creation device determines ranks for variables based on attributes, computes correlation coefficients to identify relationships, and creates databases using these relationships, reducing the need for human expertise and automating database design and maintenance processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual database design and maintenance is performed using conventional DBMS tools, then database creation and maintenance can be accomplished, but significant human effort and constant human monitoring are required leading to high costs
Solution Approach 1:
The system enables self-service database design by automatically analyzing data from multiple sources, determining relationships between variables through correlation coefficients, and generating normalized database schemas without requiring human expertise. The database creation device autonomously performs tasks that traditionally required manual database administrator intervention.
Solution Approach 2:
The patent replaces the mechanical system of manual database design with an automated computational system that uses algorithms to determine variable relationships, compute correlation coefficients, and generate database schemas. This substitution eliminates the need for human database administrators to manually design and maintain databases.
2Quantity of substance
If database volumes grow exponentially to meet business needs, then data storage capacity increases, but the complexity of maintaining and monitoring databases becomes difficult
Solution Approach 1:
The system performs preliminary normalization and relationship analysis during the database design phase, computing correlation coefficients between variables before data is loaded. This preliminary action ensures that databases are properly structured from the outset, reducing future maintenance complexity even as data volumes grow exponentially.
3Reliability
If manual error resolution in database design and maintenance is performed, then errors can be corrected, but a lot of time is consumed to resolve the errors
Solution Approach 1:
The system applies preliminary anti-action by automatically detecting and preventing database design errors before they occur. By computing correlation coefficients and determining variable relationships in advance, the system prevents improper primary key assignment and normalization errors, eliminating the need for time-consuming error resolution later.
4Productivity
If data is organized into relationships without accurate normalization, then database creation can proceed, but data integrity is affected and inconsistencies and redundancies occur
Solution Approach 1:
The system performs preliminary normalization by computing correlation coefficients between variables and determining their relationships before database creation. This preliminary action ensures that data is properly organized into normalized tables with appropriate primary and foreign keys, maintaining data integrity while enabling rapid database creation.
Data Source
AI summary
A method and device for database design and creation is disclosed. The method includes determining ranks for each of a plurality of variables in each of a plurality of databases based on at least one attribute associated with each of the plurality of variables. The method further includes arranging each of the plurality of variables in a sequence with respect to an associated database from the plurality of databases. The method includes computing a correlation coefficient between the plurality of variables across the plurality of databases based on the sequence of arrangement. The method further includes determining based on the correlation coefficient, whether a relationship exists between one or more of the plurality of variables across the plurality of databases. The method includes creating a database using the plurality of databases based on the relationship, when the relationship exists between the one or more of the plurality of variables.