Data Dependency Normalization Across Heterogeneous Ecosystems
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Solution Overview
Problem
The variability in mechanisms for tracking dependencies across electronic network environments makes it challenging to compare and normalize data dependency effects across different ecosystems, particularly for software packages with widely varying numbers of dependencies.
Innovation Solution
A system comprising a processing device configured to receive a technical business requirement document, implement a data sourcing language script, and initiate engines for data requirement traceability, data sourcing, data processing, and data lineage to normalize data dependencies by recording traceability, retrieving data, processing instructions, and generating output data, while also monitoring for changes and anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If different dependency tracking mechanisms are used across electronic network environments, then each ecosystem can maintain its own data processing methods, but it becomes challenging to compare and normalize data dependency effects across different languages and package managers
Solution Approach 1:
The patent transforms data from different dependency tracking mechanisms into a standardized format by changing parameters such as normalization factors and scaling coefficients. Each ecosystem's dependency data is adjusted using specific transformation parameters to enable consistent comparison across diverse environments while preserving the original data characteristics.
Solution Approach 2:
The patent introduces an intermediary normalization layer that sits between diverse dependency tracking mechanisms and the comparison process. This intermediary component translates various ecosystem-specific dependency representations into a common standardized format, enabling precise cross-ecosystem comparison without requiring changes to the original tracking mechanisms.
2Measurement precision
If a standardized data processing system is implemented across all ecosystems, then data dependency comparison becomes precise and consistent, but the system complexity increases to handle diverse input formats and normalization requirements
Solution Approach 1:
The patent divides the normalization system into distinct modular components: format detection modules, transformation modules, validation modules, and comparison modules. Each segment handles a specific aspect of the normalization process, reducing overall system complexity by allowing independent development, testing, and maintenance of individual components while maintaining precise cross-ecosystem comparison capabilities.
Data Source
AI summary
Systems, computer program products, and methods are described herein for normalizing data dependency effects across an electronic network environment is presented. The present invention is configured to receive a technical business requirement document (BRD) from an external source; implement a data sourcing language (DSL) script on the technical BRD; generate data processing instructions based on at least implementing the DSL on the technical BRD; initiate a data requirement traceability (DRT) engine on the data processing instructions to record the traceability between the data processing instructions and the technical BRD; initiate a data sourcing (DS) engine configured to retrieve, from authorized data sources, input data; initiate a data processing core (DPC) engine configured to implement the data processing instructions on the input data; and generate an output data based on at least implementing the data processing instructions on the input data.