17945572. SYSTEM AND METHOD FOR EXPRESSION PARSER, INVOKER AND TRANSFORMATION OF DATA simplified abstract (JPMORGAN CHASE BANK, N.A.)
Contents
- 1 SYSTEM AND METHOD FOR EXPRESSION PARSER, INVOKER AND TRANSFORMATION OF DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHOD FOR EXPRESSION PARSER, INVOKER AND TRANSFORMATION OF DATA - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEM AND METHOD FOR EXPRESSION PARSER, INVOKER AND TRANSFORMATION OF DATA
Organization Name
Inventor(s)
Hans P. Nirmal of Frisco TX (US)
SYSTEM AND METHOD FOR EXPRESSION PARSER, INVOKER AND TRANSFORMATION OF DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 17945572 titled 'SYSTEM AND METHOD FOR EXPRESSION PARSER, INVOKER AND TRANSFORMATION OF DATA
Simplified Explanation
The patent application describes methods, apparatuses, and media for data migration readiness of a target data source. A processor hosts an application on a cloud server, receives data from various data sources, defines expressions for parsing and transforming the data dynamically, validates the expressions, generates a lookup data file, parses the file, transforms the data based on the parsed lookup data file, and generates an output file in a predefined format.
- Cloud-based data migration readiness system
- Dynamic parsing and transformation of data
- Validation of expressions for data processing
- Generation of lookup data file for transformation
- Output file generation in predefined format
Potential Applications
This technology can be applied in various industries such as finance, healthcare, e-commerce, and more for efficient data migration and transformation processes.
Problems Solved
This technology solves the problem of complex data migration and transformation tasks by providing a dynamic and cloud-based solution for processing data from multiple sources.
Benefits
The benefits of this technology include faster data migration, improved data accuracy, reduced manual effort in data processing, and increased efficiency in handling large volumes of data.
Potential Commercial Applications
The technology can be commercially applied in data migration services, cloud computing solutions, data integration platforms, and software development tools for data processing.
Possible Prior Art
One possible prior art could be traditional data migration tools that require manual mapping and transformation of data, which are less efficient compared to the dynamic and cloud-based approach described in the patent application.
What are the specific industries that can benefit from this technology?
Various industries such as finance, healthcare, e-commerce, and telecommunications can benefit from this technology by streamlining their data migration and transformation processes, improving data accuracy, and increasing operational efficiency.
How does this technology compare to existing data migration tools in terms of speed and accuracy?
This technology offers faster data migration and transformation processes compared to traditional tools by dynamically parsing and transforming data on a cloud server, leading to improved accuracy and efficiency in handling large volumes of data.
Original Abstract Submitted
Various methods, apparatuses/systems, and media for data migration readiness of a target data source are disclosed. A processor hosts an application on a cloud server; receives data corresponding to the application from a plurality of types of data sources; defines expressions to be applied to the data for parsing and transforming the data dynamically on the cloud server; validates the defined expressions based on a determination that each defined expression meets a predefined threshold value; generates a lookup data file in a predefined file format in response to validating the defined expressions; parses the lookup data file; dynamically transforms the data based on the parsed lookup data file and applying the validated expressions; and generates an output file in the predefined file format for consumption after transforming the data.
