Abstract: Systems and methods described herein may improve data migration between databases that store data under different schemas. Such systems and methods may be used to transform data from a first schema (e.g., tabular, such as in relational databases) to second schema (e.g., document-based, such as in some non-relational databases). In some embodiments, data transformation for database migration may be performed using at least one rule (e.g., specified by a user) specifying a logical arrangement under the second schema for transforming a grouping of source data under the first schema. For example, tables under a tabular schema may be transformed into new documents and/or fields within documents under a document-based schema in a manner specified by the transform rule(s). In some embodiments, transforming source data in this manner permits organizing the migrated data efficiently to reduce computing resources needed to migrate the data between databases and/or for future data access operations.

Abstract: Systems and methods described herein may improve data migration between databases that store data under different schemas. Such systems and methods may be used to transform data from a first schema (e.g., tabular, such as in relational databases) to second schema (e.g., document-based, such as in some non-relational databases). In some embodiments, data transformation for database migration may be performed using at least one rule (e.g., specified by a user) specifying a logical arrangement under the second schema for transforming a grouping of source data under the first schema. For example, tables under a tabular schema may be transformed into new documents and/or fields within documents under a document-based schema in a manner specified by the transform rule(s). In some embodiments, transforming source data in this manner permits organizing the migrated data efficiently to reduce computing resources needed to migrate the data between databases and/or for future data access operations.

Abstract: Systems and methods described herein may improve data migration between databases that store data under different schemas. Such systems and methods may be used to transform data from a first schema (e.g., tabular, such as in relational databases) to second schema (e.g., document-based, such as in some non-relational databases). In some embodiments, data transformation for database migration may be performed using at least one rule (e.g., specified by a user) specifying a logical arrangement under the second schema for transforming a grouping of source data under the first schema. For example, tables under a tabular schema may be transformed into new documents and/or fields within documents under a document-based schema in a manner specified by the transform rule(s). In some embodiments, transforming source data in this manner permits organizing the migrated data efficiently to reduce computing resources needed to migrate the data between databases and/or for future data access operations.

Abstract: A computer-implemented method for automatic template selection for extracting data from an input electronic document is provided. The method includes receiving a first set of candidate templates and an input electronic document. For each candidate template, a template similarity ratio value is calculated that represents a similarity of the candidate template to the input electronic document. The first set of candidate templates are ranked according to the template similarity ratios and then matched to the input electronic document resulting in generating a normalized similarity score for each particular candidate from among the candidate templates. Differences in normalized similarity scores of successive pairs of the candidate templates is determined and a breaking point is established. A second set of candidate templates is formed by selecting candidate templates that are ranked above the breaking point. Data from the input electronic document is extracted using the second set of candidate templates.

Abstract: A computer-implemented method for automatic template selection for extracting data from an input electronic document is provided. The method includes receiving a first set of candidate templates and an input electronic document. For each candidate template, a template similarity ratio value is calculated that represents a similarity of the candidate template to the input electronic document. The first set of candidate templates are ranked according to the template similarity ratios and then matched to the input electronic document resulting in generating a normalized similarity score for each particular candidate from among the candidate templates. Differences in normalized similarity scores of successive pairs of the candidate templates is determined and a breaking point is established. A second set of candidate templates is formed by selecting candidate templates that are ranked above the breaking point. Data from the input electronic document is extracted using the second set of candidate templates.

Abstract: A computer-implemented method for automatic template selection for extracting data from an input electronic document is provided. The method includes receiving a first set of candidate templates and an input electronic document. For each candidate template, a template similarity ratio value is calculated that represents a similarity of the candidate template to the input electronic document. The first set of candidate templates are ranked according to the template similarity ratios and then matched to the input electronic document resulting in generating a normalized similarity score for each particular candidate from among the candidate templates. Differences in normalized similarity scores of successive pairs of the candidate templates is determined and a breaking point is established. A second set of candidate templates is formed by selecting candidate templates that are ranked above the breaking point. Data from the input electronic document is extracted using the second set of candidate templates.

Abstract: A computer-implemented method for automatic template selection for extracting data from an input electronic document is provided. The method includes receiving a first set of candidate templates and an input electronic document. For each candidate template, a template similarity ratio value is calculated that represents a similarity of the candidate template to the input electronic document. The first set of candidate templates are ranked according to the template similarity ratios and then matched to the input electronic document resulting in generating a normalized similarity score for each particular candidate from among the candidate templates. Differences in normalized similarity scores of successive pairs of the candidate templates is determined and a breaking point is established. A second set of candidate templates is formed by selecting candidate templates that are ranked above the breaking point. Data from the input electronic document is extracted using the second set of candidate templates.