Abstract: A system for checking data for errors, the system comprising a checking module operable to check tuples of data stored in a target database for errors, the tuples in the target database originating from the output of at least one query transformation module which applies a query transformation to tuples of data from at least one data source an identification module operable to identify a problematic tuple from a data source that produces an error in the target database, the identification module being operable to quantify the contribution of the problematic tuple in producing the error in the target database, and a description generation module operable to generate a descriptive query which represents at least one of errors identified by the checking module in the target database which are produced by the at least one query transformation module, and problematic tuples identified in a data source by the identification module.

Abstract: The optimized inequality join method is a method for joining relational tables on input inequality conditions. The optimized inequality join method is a relatively fast inequality join method using permutation arrays to store positional information for sorted attributed values. Additionally, space efficient bit arrays are used to enable optimization, such as Bloom filter indices, thus providing faster computation of the join results. The method may be used, for example, for joining various inequalities associated with a variety of measured environmental conditions for raising an alarm when certain conditions are met.

Abstract: The optimized inequality join method is a method for joining relational tables on input inequality conditions. The optimized inequality join method is a relatively fast inequality join method using permutation arrays to store positional information for sorted attributed values. Additionally, space efficient bit arrays are used to enable optimization, such as Bloom filter indices, thus providing faster computation of the join results. The method may be used, for example, for joining various inequalities associated with a variety of measured environmental conditions for raising an alarm when certain conditions are met.

Abstract: A system for checking data for errors, the system comprising a checking module operable to check tuples of data stored in a target database for errors, the tuples in the target database originating from the output of at least one query transformation module which applies a query transformation to tuples of data from at least one data source an identification module operable to identify a problematic tuple from a data source that produces an error in the target database, the identification module being operable to quantify the contribution of the problematic tuple in producing the error in the target database, and a description generation module operable to generate a descriptive query which represents at least one of errors identified by the checking module in the target database which are produced by the at least one query transformation module, and problematic tuples identified in a data source by the identification module.

Abstract: A computer implemented method for matching data records from multiple entities comprising providing respective transaction logs for the entities representing actions performed by or in respect of the entities, determining a matching score using the transaction logs for respective pairs of the entities and for predetermined combinations of merged entities by generating a measure representing a gain in behavior recognition for the entities before and after merging, and using the gain as a matching score.

Abstract: A computer-implemented method for detecting a set of inconsistent data records in a database including multiple records, comprises selecting a data quality rule representing a functional dependency for the database, transforming the data quality rule into at least one rule vector with hashed components, selecting a set of attributes of the database, transforming at least one record of the database selected on the basis of the selected attributes into a record vector with hashed components, computing a dot product of the rule and record vectors to generate a measure representing violation of the data quality rule by the record.

Abstract: A computer implemented method for correcting records in a database comprising generating, using a processor, respective candidate replacement entries for multiple inconsistent records of the database, grouping the candidate replacement entries to provide multiple groups of related candidate updates for the database, ranking the groups according to a loss function to quantify database quality, receiving input for a selected group, sorting candidate replacement entries in the selected group, and applying updates from the selected group to the database to correct entries of the inconsistent records.

Abstract: A computer-implemented method for detecting a set of inconsistent data records in a database including multiple records, comprises selecting a data quality rule representing a functional dependency for the database, transforming the data quality rule into at least one rule vector with hashed components, selecting a set of attributes of the database, transforming at least one record of the database selected on the basis of the selected attributes into a record vector with hashed components, computing a dot product of the rule and record vectors to generate a measure representing violation of the data quality rule by the record.

Abstract: A computer implemented method for matching data records from multiple entities comprising providing respective transaction logs for the entities representing actions performed by or in respect of the entities, determining a matching score using the transaction logs for respective pairs of the entities and for predetermined combinations of merged entities by generating a measure representing a gain in behavior recognition for the entities before and after merging, and using the gain as a matching score.

Abstract: A computer implemented method for correcting records in a database comprising generating, using a processor, respective candidate replacement entries for multiple inconsistent records of the database, grouping the candidate replacement entries to provide multiple groups of related candidate updates for the database, ranking the groups according to a loss function to quantify database quality, receiving input for a selected group, sorting candidate replacement entries in the selected group, and applying updates from the selected group to the database to correct entries of the inconsistent records.