Abstract: A system, method and computer-readable medium for data protection simulation and optimization in a computer network, including grouping data stored in data stores in the computer network into groupings according to an architectural or a conceptual attributes, storing, current values of risk metrics for each grouping, each of the metrics corresponding to sensitive domains, receiving a risk reduction goal corresponding to at least one risk metric in the risk metrics, the at least one risk metric corresponding to at least one sensitive domain in the sensitive domains, determining a simulated value of the at least one risk metric for each grouping in the groupings by simulating application of a protection mechanism to sensitive data in each corresponding data store, the sensitive data corresponding to the at least one sensitive domain, and ranking the groupings based on the at least one simulated value of the at least one risk metric for each grouping.

Abstract: A system, method and computer-readable medium for data protection simulation and optimization in a computer network, including grouping data stored in data stores in the computer network into groupings according to an architectural or a conceptual attributes, storing, current values of risk metrics for each grouping, each of the metrics corresponding to sensitive domains, receiving a risk reduction goal corresponding to at least one risk metric in the risk metrics, the at least one risk metric corresponding to at least one sensitive domain in the sensitive domains, determining a simulated value of the at least one risk metric for each grouping in the groupings by simulating application of a protection mechanism to sensitive data in each corresponding data store, the sensitive data corresponding to the at least one sensitive domain, and ranking the groupings based on the at least one simulated value of the at least one risk metric for each grouping.

Abstract: A system, method and computer-readable medium for missing data identification, including identifying columns in tables of a database, generating categorical columns of categorical data by transforming data values in the columns into categorical data values, generating a co-occurrence matrix corresponding to a pair of categorical columns in the categorical columns, determining an expected frequency of co-occurrence corresponding to each unique pair of categorical data values based at least in part on a marginal totals corresponding to categorical data values in the co-occurrence matrix, and identifying one or more locations of missing data based at least in part on the count of co-occurrence of each unique pair of categorical data values and the expected frequency of co-occurrence corresponding to each unique pair of categorical data values.

Abstract: A system, method and computer-readable medium for data protection simulation and optimization in a computer network, including grouping data stored in data stores in the computer network into groupings according to an architectural or a conceptual attributes, storing, current values of risk metrics for each grouping, each of the metrics corresponding to sensitive domains, receiving a risk reduction goal corresponding to at least one risk metric in the risk metrics, the at least one risk metric corresponding to at least one sensitive domain in the sensitive domains, determining a simulated value of the at least one risk metric for each grouping in the groupings by simulating application of a protection mechanism to sensitive data in each corresponding data store, the sensitive data corresponding to the at least one sensitive domain, and ranking the groupings based on the at least one simulated value of the at least one risk metric for each grouping.

Abstract: A system, method and computer-readable medium for generation of missing data including transmitting indicators corresponding to locations of missing data in columns in tables of a database, each location of missing data corresponding to categorical values of categorical columns and each location of missing data being identified based on an expected count of data values at the corresponding location, receiving a selection of at least one indicator corresponding to at least one location of missing data, the at least one location of missing data corresponding to two or more categorical values of two or more categorical columns in the categorical columns, and generating sets of data records in at least one table in the tables of the database, each set of data records having two or more column values in two or more columns that correspond to the two or more categorical values of the two or more categorical columns.

Abstract: A system, method and computer-readable medium for data protection simulation and optimization in a computer network, including grouping data stored in data stores in the computer network into groupings according to an architectural or a conceptual attributes, storing, current values of risk metrics for each grouping, each of the metrics corresponding to sensitive domains, receiving a risk reduction goal corresponding to at least one risk metric in the risk metrics, the at least one risk metric corresponding to at least one sensitive domain in the sensitive domains, determining a simulated value of the at least one risk metric for each grouping in the groupings by simulating application of a protection mechanism to sensitive data in each corresponding data store, the sensitive data corresponding to the at least one sensitive domain, and ranking the groupings based on the at least one simulated value of the at least one risk metric for each grouping.

Abstract: A system, method and computer-readable medium for data protection simulation and optimization in a computer network, including grouping data stored in data stores in the computer network into groupings according to an architectural or a conceptual attributes, storing, current values of risk metrics for each grouping, each of the metrics corresponding to sensitive domains, receiving a risk reduction goal corresponding to at least one risk metric in the risk metrics, the at least one risk metric corresponding to at least one sensitive domain in the sensitive domains, determining a simulated value of the at least one risk metric for each grouping in the groupings by simulating application of a protection mechanism to sensitive data in each corresponding data store, the sensitive data corresponding to the at least one sensitive domain, and ranking the groupings based on the at least one simulated value of the at least one risk metric for each grouping.

Abstract: A system, method and computer-readable medium for generation of missing data including transmitting indicators corresponding to locations of missing data in columns in tables of a database, each location of missing data corresponding to categorical values of categorical columns and each location of missing data being identified based on an expected count of data values at the corresponding location, receiving a selection of at least one indicator corresponding to at least one location of missing data, the at least one location of missing data corresponding to two or more categorical values of two or more categorical columns in the categorical columns, and generating sets of data records in at least one table in the tables of the database, each set of data records having two or more column values in two or more columns that correspond to the two or more categorical values of the two or more categorical columns.

Abstract: A system, method and computer-readable medium for missing data identification, including identifying columns in tables of a database, generating categorical columns of categorical data by transforming data values in the columns into categorical data values, generating a co-occurrence matrix corresponding to a pair of categorical columns in the categorical columns, determining an expected frequency of co-occurrence corresponding to each unique pair of categorical data values based at least in part on a marginal totals corresponding to categorical data values in the co-occurrence matrix, and identifying one or more locations of missing data based at least in part on the count of co-occurrence of each unique pair of categorical data values and the expected frequency of co-occurrence corresponding to each unique pair of categorical data values.