Abstract: A method for reading the altered data field in accordance with the field alteration data is provided. The method may include altering a data field characteristic of a data field in a data table, saving the field alteration datum associated with the alteration in a data storage facility, submitting a query requiring the use of the data field in the dataset and reading the altered data field in accordance with the field alteration data. The alteration may generate a field alteration datum and a component of the query may consist of reading the field alteration data.

Abstract: In embodiments of the present invention improved capabilities are described for using an analytic platform to obtain a projection, where a user of an analytic platform may select at least one dimension on which the user wishes to make a projection from the data set. A core information matrix may be developed for data set, where the core information matrix may include regions representing the statistical characteristics of alternative projection techniques that may be applied to the data set, and may include statistical characteristics relating to projections using any selected dimensions. In addition, a user interface may be provided whereby a user may observe the regions of the core information matrix to facilitate selecting an appropriate projection technique.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.

Abstract: A computer system and method is disclosed that analyzes and corrects retail data. The system and method includes several client workstations and one or more servers coupled together over a network. A database stores various data used by the system. A business logic server uses competitive and complementary fusion to analyze and correct some of the data sources stored in database server. The data fusion process itself is an iterative one—utilizing both competitive and complementary fusion methods. In competitive fusion, two or more data sources that provide overlapping attributes are compared against each other. More accurate/reliable sources are used to correct less accurate/reliable sources. In complementary fusion, relationships modeled where data sources overlap are projected to areas of the data framework in which fewer sources exist—enhancing the accuracy/reliability of those fewer sources even in the absence of the other sources upon which the models were based.