Generic ETL Processor for Multi-Format Data Handling
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Solution Overview
Problem
Conventional data processing tools struggle to efficiently handle and process a vast amount of data with various file formats from multiple sources, leading to high manual effort, technical risks, and delays in financial reporting processes.
Innovation Solution
A platform, language, cloud, and database agnostic data processing module that implements a generic single ETL processor, allowing for the configuration and loading of multiple files with different formats and structures without requiring additional technical development, and enabling user-controlled data loads through a UI mapping system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If one ETL is built per file to handle different formats and structures, then data processing accuracy is improved, but device complexity and development time increase significantly
Solution Approach 1:
The patent implements a universal ETL processor that can handle multiple file formats and structures through a single system. The processor uses configurable templates and metadata-driven approaches to adapt to different data sources (Excel, CSV, JSON, XML) without requiring separate ETL developments for each file type, thereby reducing complexity while maintaining processing accuracy
Solution Approach 2:
The system changes parameters dynamically based on file metadata and format detection. By adjusting processing parameters according to the specific file type and structure encountered, the single ETL processor can accurately handle diverse data formats without manual reconfiguration or separate ETL programs for each format
2Adaptability or versatility
If manual file preparation and loading is performed, then flexibility in handling different formats is improved, but productivity and processing speed deteriorate
Solution Approach 1:
The ETL processor implements self-service capabilities by automatically detecting file formats, validating data structures, and configuring processing parameters without manual intervention. The system autonomously handles format flexibility through metadata inspection and automatic adaptation, eliminating the need for manual file preparation while maintaining high processing speed
Solution Approach 2:
The system performs preliminary actions by pre-configuring processing templates and validation rules for different file formats before actual data processing begins. This preliminary setup enables the system to quickly adapt to various formats during production processing without sacrificing speed, as the adaptation logic is already prepared and configured
3Ease of operation
If conventional data processing tools are used, then ease of operation is maintained, but ability to handle vast amounts of diverse data deteriorates
Solution Approach 1:
The patent introduces an intermediary layer between the user interface and the data processing engine. This intermediary handles the complexity of diverse data format processing, metadata management, and format detection automatically, allowing users to operate the system simply while the intermediary manages the complex adaptation to various data formats and structures
Data Source
AI summary
Various methods and processes, apparatuses/systems, and media for processing of multiple files having different formats and structures are disclosed. The method includes identifying a plurality of data files each having a predefined file format and structure and viewing corresponding file status. The plurality of data files being received from various data sources. The method implements a generic single ETL processor for front loading of ETL in a manner such that user input is received to configure the plurality of files and transmit to multiple downstream systems for further processing via UI mapping. Data file configuration screen can be used to search list of files configured under any report masters along with its status. This configuration screen can be also used to configure new external source files or edit an existing one thereby providing, among others, user controlled data loads, reducing tech dependency, providing reusability and scalability, and eliminating manual overrides.