Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

Abstract: Correcting data in a dataset. A set of data tokens from a tabular data store are grouped into a plurality of different clusters based on similarity of tokens. A reference cluster is selected from among the plurality of different clusters such that the plurality of clusters includes a reference cluster and one or more other clusters. One or more tokens in the one or more other clusters are transformed. The effect on the reference cluster of adding the transformed tokens to the reference cluster is determined. Using this information, a correction for a token in the dataset is identified. The data store is updated to correct the token using the identified correction.

Abstract: Correcting data in a dataset. A set of data tokens from a tabular data store are grouped into a plurality of different clusters based on similarity of tokens. A reference cluster is selected from among the plurality of different clusters such that the plurality of clusters includes a reference cluster and one or more other clusters. One or more tokens in the one or more other clusters are transformed. The effect on the reference cluster of adding the transformed tokens to the reference cluster is determined. Using this information, a correction for a token in the dataset is identified. The data store is updated to correct the token using the identified correction.

Abstract: Correcting data in a dataset. A set of data tokens from a tabular data store are grouped into a plurality of different clusters based on similarity of tokens. A reference cluster is selected from among the plurality of different clusters such that the plurality of clusters includes a reference cluster and one or more other clusters, one or more tokens in the one or more other clusters are transformed. Transforming tokens is performed based on a cost of transforming tokens. The effect on the reference cluster of adding the transformed tokens to the reference cluster is determined. Using this information, a correction for a token in the dataset is identified. The data store is updated to correct the token.

Abstract: During migration of data from at least one data source to a target system, data quality is determined by obtaining metadata associated with the target system, automatically generating instantiated rules for assessing a quality of data to be loaded from the at least one data source into the target system, where the instantiated rules are dependent upon the obtained metadata associated with the target system, and applying a quality analysis based upon the instantiated rules to the data to be loaded into the target system. The quality analysis provides an indication of a level of compliance of the data with requirements of the target system.

Abstract: Correcting data in a dataset. A set of data tokens from a tabular data store are grouped into a plurality of different clusters based on similarity of tokens. A reference cluster is selected from among the plurality of different clusters such that the plurality of clusters includes a reference cluster and one or more other clusters, one or more tokens in the one or more other clusters are transformed. Transforming tokens is performed based on a cost of transforming tokens. The effect on the reference cluster of adding the transformed tokens to the reference cluster is determined. Using this information, a correction for a token in the dataset is identified. The data store is updated to correct the token.

Abstract: During migration of data from at least one data source to a target system, data quality is determined by obtaining metadata associated with the target system, automatically generating instantiated rules for assessing a quality of data to be loaded from the at least one data source into the target system, where the instantiated rules are dependent upon the obtained metadata associated with the target system, and applying a quality analysis based upon the instantiated rules to the data to be loaded into the target system. The quality analysis provides an indication of a level of compliance of the data with requirements of the target system.