Source Data Transformation to Business Objects
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Solution Overview
Problem
Existing data transfer solutions from a source to a target destination are inefficient, as they require multiple database replicates, extensive processing, and transformation at the target destination, leading to high costs, latency, and resource bottlenecks, while transferring irrelevant data and relying heavily on target destination infrastructure.
Innovation Solution
A computerized system that connects to a source database, queries and organizes data based on business-defined rules, transforms it into a ready-to-consume business object at the source, and publishes it as a packet in a text or binary format, decoupling the source from the target and minimizing unnecessary data transfer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If log-mining solution is used for real-time processing or replication of the entire database, then data can be transferred from source to target destination, but large amounts of irrelevant data are transferred, analyzed and filtered at the target destination which is time consuming and costly
Solution Approach 1:
The patent applies preliminary action by transforming data into business objects at the source system before transfer, rather than at the target destination. The source system proactively creates ready-to-consume business objects and publishes them to a message broker, eliminating the need for time-consuming transformation processes at the target destination.
Solution Approach 2:
The patent extracts only the necessary business objects from the source database based on query criteria, rather than replicating entire databases. The system identifies and extracts specific data elements that match query conditions, transforming them into business objects before transfer, thus avoiding transfer of irrelevant data.
2Ease of operation
If the replicated database is transformed by further systems into the business object at the target destination, then the database can be converted into usable form, but the processing is prone to errors and depends heavily on the processing at the target destination
Solution Approach 1:
The patent inverts the traditional transformation approach by performing data transformation at the source system instead of at the target destination. The source system transforms raw database data into business objects before transfer, reversing the conventional flow where target systems perform transformation after receiving replicated databases.
Solution Approach 2:
The source system performs self-service by autonomously transforming its own data into business objects and publishing them to the message broker. This eliminates dependency on target destination processing capabilities and knowledge, as the source system independently prepares data in usable form.
3Adaptability or versatility
If several tools are used to transform the content of the databases into the business object, then the transformation can be performed, but the solution is tightly coupled with the target destination system and requires multiple transformation steps
Solution Approach 1:
The patent implements universality by creating a standardized business object format that can be consumed by multiple different target systems. The message broker serves as a universal intermediary that can route business objects to various destinations without requiring custom transformation tools for each target system.
Solution Approach 2:
The patent introduces a message broker as an intermediary between the source and target systems. The source system publishes business objects to the message broker, which then distributes them to target systems. This intermediary decouples the source from specific target systems, eliminating the need for tight coupling and multiple specialized transformation tools.
Data Source
AI summary
A method of connecting, by a computerized system, to a database at a source is disclosed. The computerized system queries the database for data associated with a characteristic and identifies the data. The computerized system organizes the data into a batch based on business-defined rules. The batch condenses a plurality of rows of data in the database associated with the characteristic into one row of data associated with the characteristic. The computerized system transforms the batch into a packet having a text or binary ready-to-consume format and publishes the packet as a ready-to-consume business object.


