Database Analytics via Embedded Anadigits
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Solution Overview
Problem
Conventional database management systems require additional software development and computing resources to generate analytics, making it inefficient to monitor and analyze data traffic within the database system.
Innovation Solution
Integrating analytics directly into the database by storing metadata in additional bytes (anadigits) within each data line, allowing for real-time tracking and retrieval of analytics data without the need for external tools, enabling users to query the database for insights on data popularity and user behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If analytics are gathered by monitoring traffic using external software, then analytics data can be obtained, but additional software development, computing resources, and time are required
Solution Approach 1:
The patent merges the analytics functionality directly into the database management system by integrating an analytics module within the database. This consolidation eliminates the need for separate external monitoring software, reducing device complexity while maintaining analytics data collection capabilities. The database system now performs both data storage and analytics functions through a unified architecture.
Solution Approach 2:
The database management system is enhanced to perform multiple functions: traditional data storage and retrieval, plus built-in analytics processing. The analytics module within the database can monitor traffic, generate insights, and provide data packages without requiring external specialized software, making the system more universal and self-sufficient.
2Productivity
If external software is used to monitor database traffic, then analytics can be generated, but additional computing resources and time are consumed
Solution Approach 1:
By merging analytics processing into the database management system, the patent eliminates redundant data transmission and processing between external systems. The analytics module accesses data directly within the database, reducing computing overhead and resource consumption while improving analytics generation productivity.
Solution Approach 2:
The analytics module acts as an intermediary within the database system, processing data locally without requiring external software intervention. This internal mediator reduces the computational burden on external systems and optimizes resource usage by handling analytics generation within the database's own computing infrastructure.
3Loss of information
If analytics data is stored externally, then data can be analyzed, but additional software and resources are required
Solution Approach 1:
The patent combines analytics data storage with the primary database system. Analytics results are stored within the database alongside operational data, eliminating the need for separate external storage systems. This integration simplifies operations by providing a single point of access for both operational and analytics data.
Solution Approach 2:
The database system becomes a universal platform that handles both operational data storage and analytics data storage. Users can retrieve both types of data through the same interface and system, improving ease of operation and eliminating the complexity of managing multiple separate systems.
Data Source
AI summary
A computer-implemented method for receiving, at a database, an analytics request associated with a selected data line from a database and reading a set of additional bytes from the database corresponding to the selected data line. The method may further include parsing and formatting the set of additional bytes read from the database to generate, at the database, an analytics reply to the analytics request, where each of a plurality of data lines in the database represents a search query and where the analytics data comprises a number of search query requests on a subject matter and a number of search query requests for private data.