Enterprise Framework for Workflow Data Distribution
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Solution Overview
Problem
Current software deployment processes are inefficient and lack a standardized framework for transforming proprietary workflow management data into a relational format for downstream applications, leading to data reconciliation challenges, duplication, and non-compliance with Enterprise Data Management Plan standards.
Innovation Solution
An enterprise framework utilizing a Software Deployment Management (SDM) environment with a Consumer Data Provisioning Point (CDPP) automation agent to extract and model workflow data from proprietary formats into standardized relational format for near-real-time distribution, eliminating human input and data duplication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If proprietary workflow management output format is used for data storage, then data can be stored in vendor-specific format, but data transformation to relational format requires many manual steps and developer intervention
Solution Approach 1:
The patent introduces an intermediary translation layer between the proprietary workflow management system and downstream applications. This intermediary component automatically translates proprietary format data into relational format, eliminating the need for manual transformation steps and reducing developer intervention while maintaining compatibility with existing systems.
Solution Approach 2:
The system implements self-service automation where the workflow management system automatically performs data transformation and distribution without requiring manual developer steps. The automated processes include extracting data from proprietary format, transforming to relational format, and distributing to downstream applications, thereby reducing complexity and improving ease of manufacture.
2Reliability
If manual data transformation process is used, then data can be transformed from proprietary format to relational format, but data duplication and reconciliation challenges occur
Solution Approach 1:
The patent implements continuous automated data transformation and distribution processes that eliminate manual intervention gaps. The system continuously extracts data from the workflow management system, transforms it to relational format, and distributes it to downstream applications in real-time or near-real-time, ensuring data consistency and eliminating reconciliation challenges while reducing transformation time.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor data transformation and distribution processes, automatically detecting and correcting reconciliation issues. The feedback loop ensures data integrity by verifying that transformed data matches source data and that downstream applications receive accurate relational format data, thereby improving reliability without increasing time loss.
3Productivity
If standardized relational format is implemented for downstream consumption, then data distribution becomes efficient and compliant with EDMP standards, but requires automated transformation framework
Solution Approach 1:
The patent implements a universal automated transformation framework that handles multiple data types, formats, and downstream applications through a single standardized relational format interface. This multi-functional system can transform various proprietary workflow formats into standardized relational data and distribute to different downstream applications, improving productivity while managing complexity through standardization.
Solution Approach 2:
The system utilizes parameter changes in data format transformation, converting proprietary format parameters into standardized relational format parameters automatically. The transformation framework dynamically adjusts data structure parameters, data types, and relationships to match EDMP standards, enabling efficient standardized distribution while the automation manages the complexity of parameter transformations.
Data Source
AI summary
A system and methods for an enterprise framework for efficient and adaptable workflow application data distribution using a Software Deployment Management (SDM) environment are described. Workflow data is received by the system from a workflow management application and modeled for downstream use. Use of a consumer data provisioning point (CDPP) agent includes utilization of a central control table that assists with the extraction, transformation and loading of workflow data from a proprietary format to a modeled relational forma. An end to end (E2E) automation process is controlled by the CDPP agent which facilitates extraction of data from upstream applications with configurable frequency for the transformed data. Embodiments of the invention provide efficiency improvements by automating numerous steps and eliminating the need for human input for various steps in the process of workflow data distribution and enable near-real-time data distribution and analytics.