Software Application Data Aggregation for Unified Operations Insights
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Solution Overview
Problem
In a computer-networked environment, the fragmented storage of data across multiple databases with disparate specifications makes it difficult for stakeholders to gain a unified view of operations, leading to limited visibility and challenges in identifying performance issues, as critical information is dispersed in inconsistent formats, complicating manual reporting and decision-making.
Innovation Solution
A system aggregates data from multiple sources using machine learning models, transforming and normalizing data formats, applying ML models for analysis, and generating visualizations to provide insights and analytics, thereby automating the detection of performance issues across the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple databases with disparate specifications, then each database can be optimized for specific functions, but it becomes difficult to gain a unified view of operations and identify performance issues
Solution Approach 1:
The patent introduces a data aggregation service as an intermediary layer between multiple databases and users. This service retrieves data from various databases, transforms it into a unified format, and presents it through a consistent interface. The intermediary resolves the contradiction by maintaining the specialized structure of individual databases while providing a unified view through the aggregation layer, eliminating the need for users to directly access disparate database structures.
Solution Approach 2:
The system segments data access into two distinct layers: the data storage layer maintains separate optimized databases for different functions, while the data aggregation layer provides unified access. This segmentation allows each database to remain optimized for its specific purpose while the aggregation layer handles the complexity of integrating data from multiple sources, resolving the contradiction between specialization and unification.
2Measurement precision
If users access individual databases manually to retrieve data, then data can be retrieved from specific sources, but the process becomes tedious and time-consuming when gathering holistic information across multiple applications
Solution Approach 1:
The data aggregation service performs preliminary actions by automatically retrieving, transforming, and consolidating data from multiple databases before users need to access it. The service pre-processes data into unified formats and stores it in an accessible aggregation database, eliminating the need for users to manually query multiple sources. This preliminary action significantly reduces time while maintaining measurement precision through automated data transformation.
3Quantity of substance
If data is retrieved from multiple databases, then comprehensive information can be gathered, but the data may not be ready for immediate use due to different formatting and storage specifications
Solution Approach 1:
The patent applies parameter changes by transforming data from various formats and specifications into a unified, standardized format. The data aggregation service modifies data parameters (structure, format, types) to match a consistent schema, making all retrieved data immediately usable. This parameter transformation resolves the contradiction by maintaining comprehensive information volume while ensuring data readiness through automated formatting standardization.
Data Source
AI summary
One or more configurations associated with a plurality of software applications within a distributed computing infrastructure are obtained. First resource data associated with the plurality of software applications is received from a variety of data sources within the distributed computing infrastructure. This first resource data, in different formats, is then transformed into second resource data in a standardized format. The second resource data is integrated into a data source using the obtained configurations. In response to an indication of one or more data points corresponding to the second resource data, one or more portions of the second resource data are transformed.