Abstract: The system obtains metadata associated with physical data and metadata associated with a semantic model and converts the metadata associated with the physical data into a first embedding vector and the metadata associated with the semantic model into a second embedding vector. The system determines a measure of similarity between the first embedding vector and the second embedding vector in the multidimensional space, and obtains a threshold associated with the measure of similarity. The system compares the measure of similarity with the threshold to determine whether to create a mapping between the physical data and the category associated with the semantic model. Based on the comparison, the system creates the mapping between the physical data and the category.

Abstract: A computer-implemented method and system for comparing and analyzing similarities between database tables. The method includes receiving a database instance containing at least two tables with multiple rows and columns, performing irreversible hashing operations on selected data within specified rows and columns of both tables, conducting statistical comparisons between corresponding columns to determine table similarities, and displaying the comparison results through a graphical user interface. The system employs data transformation through one-way hashing techniques and statistical analysis to evaluate structural and content similarities between database tables, enabling efficient comparison of structured data sets while maintaining data security through irreversible hashing.

Abstract: A computer-implemented method and system for comparing and analyzing similarities between database tables. The method includes receiving a database instance containing at least two tables with multiple rows and columns, performing irreversible hashing operations on selected data within specified rows and columns of both tables, conducting statistical comparisons between corresponding columns to determine table similarities, and displaying the comparison results through a graphical user interface. The system employs data transformation through one-way hashing techniques and statistical analysis to evaluate structural and content similarities between database tables, enabling efficient comparison of structured data sets while maintaining data security through irreversible hashing.