Snowflake inc. (20240345998). CONVERTING DATAFRAMES TO RELATIONAL DATABASES simplified abstract
Contents
CONVERTING DATAFRAMES TO RELATIONAL DATABASES
Organization Name
Inventor(s)
Balachander Atur of Redwood WA (US)
Hazem Elmeleegy of Sunnyvale CA (US)
Jung Lin Lee of El Dorado CA (US)
Aditya G. Parameswaran of Berkeley CA (US)
Devin Petersohn of Liberty MO (US)
Mahesh Shankar Vashishtha of Madison WI (US)
CONVERTING DATAFRAMES TO RELATIONAL DATABASES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240345998 titled 'CONVERTING DATAFRAMES TO RELATIONAL DATABASES
The abstract of this patent application describes systems and methods for converting dataframes to relational databases and vice versa.
- Store information representing a first dataframe
- Generate a first relation with a first schema representing the first dataframe
- Add a first ordering attribute to the first relation
- Populate the first ordering attribute with row numbers from the first dataframe
- Perform relational database operations to modify the first relation into a second relation
- Create a second dataframe based on the second relation while preserving row labels and order
Potential Applications: - Data management systems - Database migration tools - Data analysis software
Problems Solved: - Efficient conversion between dataframes and relational databases - Preserving data integrity during conversion processes
Benefits: - Streamlined data conversion processes - Improved data organization and storage - Enhanced data analysis capabilities
Commercial Applications: Title: "Dataframe to Relational Database Conversion Technology for Enhanced Data Management" This technology can be utilized in various industries such as finance, healthcare, and e-commerce for efficient data handling and analysis.
Questions about Dataframe to Relational Database Conversion Technology: 1. How does this technology improve data management processes?
- This technology streamlines the conversion of data between dataframes and relational databases, enhancing data organization and analysis capabilities.
2. What are the potential applications of this technology in different industries?
- This technology can be applied in finance, healthcare, e-commerce, and other sectors for improved data handling and analysis.
Original Abstract Submitted
systems and methods for converting dataframes to relational databases and/or vice versa, are disclosed. exemplary implementations may: store information that represents a first dataframe; generate a first relation that represents the first dataframe, the first relation having a first schema; add a first ordering attribute to the set of attributes of the first relation; populate the first ordering attribute with numbers in accordance with a row numbering of the first dataframe; perform a relational database operation on the first relation that modifies the first relation into a second relation; create a second dataframe based on the second relation such that the row labels and the order of the rows are preserved for the (remaining) records and attributes of the second relation; and/or perform other steps.
