Method and system for performing data manipulations associated with business processes and operations

Abstract

A method and apparatus for accessing, processing and manipulating data in an OLAP database. According to one aspect, the present invention comprises a user interface configured for accessing, processing and manipulating data in an OLAP cube. According to another aspect, the present invention comprises a calculation engine for manipulating and managing data in the OLAP cube.

What is claimed is: 
     
         1 . A system for processing data in an OLAP database, said system comprising:
 a user interface module;   a calculation engine;   said user interface comprising a screen configured for specifying a data process to be performed on data in the OLAP database in response to one or more user inputs; and   said calculation engine being configured to interface to the OLAP database and execute said data process and generate a data process output.   
     
     
         2 . The system as claimed in  claim 1 , wherein said user interface module comprises a data transformation screen, said data transformation screen being configured for specifying the data process according to one or more dimensions, wherein each of said one or more dimensions comprises a characterization of data stored in the OLAP database. 
     
     
         3 . The system as claimed in  claim 2 , wherein said one or more dimensions include one or more common dimensions and each said one or more common dimensions comprises a plurality of members, and one or more non-common dimensions and each of said one or more non-common dimensions comprises a plurality of members. 
     
     
         4 . The system as claimed in  claim 3 , wherein said data process includes a user inputted data value, and said calculation engine is configured to manipulate data in the OLAP database based on said inputted data value. 
     
     
         5 . The system as claimed in  claim 3 , wherein said calculation engine is configured to manipulate data in the OLAP database for selected common dimension members based on a combination of said associated common dimensions. 
     
     
         6 . The system as claimed in  claim 3 , wherein said non-common dimension includes one or more source-target dimensions for specifying data to be manipulated, and said source-target dimensions comprising one or more source members and one or more target members, wherein said one or more source members identify data to be accessed from the OLAP database, and wherein said one or more target members identify data to be written back to the OLAP database. 
     
     
         7 . The system as claimed in  claim 6 , wherein said source-target dimensions comprise time-based target dimensions and non-time based target dimensions. 
     
     
         8 . The system as claimed in  claim 7 , wherein said user interface includes a screen configured for selecting one or more of said common dimensions for a data process or one or more of said source-target dimensions, and said screen including input controls responsive to user input for selecting said one or more of said source members or said target members. 
     
     
         9 . The system as claimed in  claim 8 , wherein said data transformation screen is configured to provide an aggregation option associated with the members of said source-target dimension, and said aggregation option comprising one of an aggregate operation, an average including empty values operation, an average excluding empty values operation, or a copy between time members operation. 
     
     
         10 . The system as claimed in  claim 9 , wherein said data transformation screen is configured to provide a delete data from source operation, and said delete data from source operation being responsive to a user input. 
     
     
         11 . The system as claimed in  claim 9 , wherein said data transformation screen is configured to provide a source data operation, and said source data operation comprising one of an increase by percentage operation, a decrease by operation, an increase by absolute amount operation, a decrease by absolute amount operation, or a multiply by amount operation. 
     
     
         12 . The system as claimed in  claim 9 , wherein said data transformation screen is configured to provide a target data write operation, and said target data write operation comprising one of an overwrite existing data operation, an add to existing data operation, or a subtract from existing data operation. 
     
     
         13 . The system as claimed in  claim 9 , wherein said data transformation screen is configured to provide a time spread operation for allocating data along a time target dimension, and said time spread operation comprising one of a store value to leaf members operation, a spread based on existing data operation, a spread based on data in a member property dimension, or a spread evenly operation. 
     
     
         14 . The system as claimed in  claim 9 , wherein said data transformation screen is configured to provide a data spread operation for allocating data along a non-time target dimension, and said data spread operation comprising one of a store value to leaf members operation with no spread, a spread based on existing data operation, a spread based on data in a member property dimension, or a spread evenly operation. 
     
     
         15 . The system as claimed in  claim 14 , wherein said data spread operation is configured for a data value specified by a user. 
     
     
         16 . The system as claimed in  claim 2 , wherein said user interface includes a processing exception screen, and said processing exception screen being configured to provide a processing options for one or more processing exceptions. 
     
     
         17 . The system as claimed in  claim 16 , wherein said processing exceptions comprise a spread on zero condition, and said processing options comprise one of a spread evenly without a warning operation, a spread evenly with a warning operation, a skip member combination without a warning operation, a skip member combination with a warning operation, or an abort process operation. 
     
     
         18 . The system as claimed in  claim 16 , wherein said processing exceptions comprise a dimension spread invalid value handing condition, and said processing options comprise one of a spread evenly without a warning operation, a spread evenly with a warning operation, a skip member combination without a warning operation, a skip member combination with a warning operation, or an abort process operation. 
     
     
         19 . The system as claimed in  claim 2 , wherein said calculation engine is configured to execute one or more of a store data based on existing data operation, a store single data value operation, or an allocate single data value operation. 
     
     
         20 . The system as claimed in  claim 2 , wherein said calculation engine is configured to generate a contra account entry, and said data transformation screen is configured for a user to specify data for said contra account entry. 
     
     
         21 . A computer-implemented method for processing data stored in an OLAP cube, said method comprising the steps of:
 characterizing data in the OLAP cube according to a common dimension, and said common dimension comprising one or more common dimension members;   characterizing data in the OLAP cube according to a non-common dimension, and said non-common dimension comprising one or more non-common dimension members;   specifying a combination comprising selected common dimension members and selected non-common dimension members;   selecting cells in the OLAP cube based on said specified combination, and reading data from said selected cells;   applying a processing operation to the data read from said selected cells; and   writing data from said processing operation back to the OLAP cube.   
     
     
         22 . The method as claimed in  claim 21 , wherein said non-common dimensions include one or more of a source-target dimensions, and said source-target dimensions comprise one or more source members and one or more target members, wherein said one or more source members identify data to be accessed from the OLAP database, and wherein said one or more target members identify data to be written back to the OLAP database. 
     
     
         23 . The method as claimed in  claim 22 , wherein said processing operation comprises one of an allocate based on existing operation, a store single data value operation, or an allocate single data value operation. 
     
     
         24 . The method as claimed in  claim 22 , wherein said source-target dimensions comprise time-based target dimensions and non-time based target dimensions. 
     
     
         25 . The method as claimed in  claim 21 , wherein said step of writing data comprises one of overwriting existing data in the OLAP cube with data from said processing operation, adding data from said processing operation to existing data in the OLAP cube, or subtracting data from said processing operation to existing data in the OLAP cube. 
     
     
         26 . A computer program product for processing data in an OLAP database, said computer program product comprising:
 a storage medium configured to store computer readable instructions;   said computer readable instructions including instructions for,   characterizing data in the OLAP cube according to a common dimension, and said common dimension comprising one or more common dimension members;   characterizing data in the OLAP cube according to a non-common dimension, and said non-common dimension comprising one or more non-common dimension members;   specifying a combination comprising selected common dimension members and selected non-common dimension members;   selecting cells in the OLAP cube based on said specified combination, and reading data from said selected cells;   applying a processing operation to the data read from said selected cells; and   writing data from said processing operation back to the OLAP cube.