US20180285436A1 - Method and system for performing data manipulations associated with business processes and operations - Google Patents

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.

Description

FIELD OF THE INVENTION
• The present invention relates to computer systems and more particularly, to a method and system for performing data manipulations and data processing associated with financial and/or operational data stored in a database.
BACKGROUND OF THE INVENTION
• Online analytical processing or OLAP is a technique in business intelligence applications and comprises providing answers to analytical queries that are multidimensional in nature. Examples of OLAP applications include business reporting for sales, marketing, management reporting, business process management, budgeting and forecasting, financial reporting and the like.
• Databases configured for OLAP applications typically comprise a multidimensional data model, often referred to as a “cube”. A multidimensional data model allows for complex analytical queries with rapid execution time. The cube structure comprises aspects of navigational databases and hierarchical databases.
• An OLAP cube can be thought of as an extension of the two-dimensional array of a spreadsheet, and comprises dimensions. In the context of an OLAP cube, dimensions provide additional methods for analyzing data. For example, an OLAP cube can be configured to allow a company to analyze financial data by product, by time-period, by city, by type of revenue and cost, and by comparing actual data with a budget. In a further aspect, a user, for example, a financial analyst, may want to view the data in various ways, such as displaying all the cities down the page and all the products across a page. This could be for a specified period, version and type of expenditure. Having seen the data in this particular way the analyst might then immediately wish to view it in another way. The cube structure provides the capability to re-orient the display so that the data displayed now had periods across the page and type of cost down the page. Because this re-orientation involved re-summarizing very large amounts of data, this new view of the data had to be generated efficiently to avoid wasting the analyst's time, i.e. within seconds, rather than the hours a relational database and conventional report-writer might have taken.
• According to another aspect, data in a cube may be updated at times, perhaps by different people. Techniques are therefore often needed to lock parts of the cube while one of the users is writing to it and to recalculate the cube's totals. Other facilities may allow an alert that shows previously calculated totals are no longer valid after the new data has been added, but some products only calculate the totals when they are needed.
• It will be appreciated that while an OLAP cube provides a flexible and multidimensional structure data model, there remains a need in the art for improvements, such as, applications including data acquisition and processing techniques capable of exploiting the capabilities of an OLAP cube.
SUMMARY OF THE INVENTION
• The present invention provides a method and system for accessing data, configuring data processing and manipulations involving the data. According to an embodiment, the data comprises information associated business processes and operations stored in an OLAP database.
• According to one aspect, there is provided a system for processing data in an OLAP database, the system comprises: a user interface module; a calculation engine; the 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 the calculation engine being configured to interface to the OLAP database and execute the data process and generate a data process output.
• According to another aspect, there is provided a computer-implemented method for processing data stored in an OLAP cube, the method comprises the steps of: characterizing data in the OLAP cube according to a common dimension, and the common dimension comprising one or more common dimension members; characterizing data in the OLAP cube according to a non-common dimension, and the 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 the specified combination, and reading data from the selected cells; applying a processing operation to the data read from the selected cells; and writing data from the processing operation back to the OLAP cube.
• According to a further aspect, there is provided a computer program product for processing data in an OLAP database, the computer program product comprises: a storage medium configured to store computer readable instructions; the computer readable instructions including instructions for, characterizing data in the OLAP cube according to a common dimension, and the common dimension comprising one or more common dimension members; characterizing data in the OLAP cube according to a non-common dimension, and the 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 the specified combination, and reading data from the selected cells; applying a processing operation to the data read from the selected cells; and writing data from the processing operation back to the OLAP cube.
• Other aspects and features of the present invention will become apparent to those ordinarily skilled in the art upon review of the following description of embodiments of the invention in conjunction with the accompanying figures.
BRIEF DESCRIPTION OF THE DRAWINGS
• Reference will now be made to the accompanying drawings which show, by way of example, embodiments of the present invention, and in which:
• FIG. 1 shows in diagrammatic form an exemplary system for operating or executing methods or processing in accordance with an embodiment of the invention;
• FIG. 2 is an exemplary screen shot of a process configured to specify a cube and one or more operations associated with the cube, according to an embodiment of the invention;
• FIG. 3 is an exemplary screen shot of a process configured to select common dimensions and/or dimensions for a cube in accordance with an embodiment of the invention;
• FIG. 4 is an exemplary screen shot of a process configured to select source and/or target members of non-common dimensions for a cube in accordance with an embodiment of the invention;
• FIGS. 5A and 5B are exemplary screen shots of a process configured to specify data transformation operations for a cube in accordance with an embodiment of the invention;
• FIG. 6 is an exemplary screen shot of a process configured to specify the handling of processing exceptions;
• FIG. 7 shows in flowchart form a process for calculating processes in accordance with an embodiment the present invention;
• FIG. 8 shows in flowchart form a process for reading data from a cube and determining an average value in accordance with an embodiment the present invention;
• FIG. 9 shows in flowchart form a process for determining adjustments to data read from a cube in accordance with an embodiment of the present invention;
• FIG. 10 shows in flowchart form a process for managing the allocation of data to a cube based on a time dimension in accordance with an embodiment of the present invention;
• FIGS. 11A and 11B show in flowchart form a process for determining time allocation parameters in accordance with an embodiment of the present invention;
• FIG. 12 shows in flowchart form a process for calculating data allocations across a time dimension in accordance with an embodiment of the present invention;
• FIG. 13 shows in flowchart form a process for managing data allocations across non-time dimensions in accordance with an embodiment of the present invention;
• FIGS. 14A and 14B show in flowchart form a process for determining non-time allocation parameters in accordance with an embodiment of the present invention;
• FIG. 15 shows in flowchart form a process for calculating allocated data for allocations across non-time dimensions in accordance with an embodiment of the present invention;
• FIG. 16 shows in flowchart form a process for storing data in a cube in accordance with an embodiment of the present invention;
• FIG. 17 shows in flowchart form a process for copying data between time members in the cube in accordance with an embodiment of the present invention;
• FIG. 18 shows in flowchart form a process for managing the deletion of source data and generation of contra account entries in accordance with an embodiment of the present invention; and
• FIGS. 19A and 19B show in flowchart form a process for calculating contra account entries in accordance with an embodiment of the present invention.
• Like reference numerals indicate like or corresponding elements or components in the drawings.
DETAILED DESCRIPTION OF THE EMBODIMENTS OF THE INVENTION
• Embodiments according to the present invention are described in the context of data or information used by companies for planning, budgeting, monthly financial reporting and/or consolidation of financial results. In the context of the present description, numerical data is stored in an OLAP database, and comprises one or more cubes. Each cube comprises a structure based on dimensions and members.
• The cubes and dimensions will vary from company to company. In addition, the names of dimensions within cubes can vary. For instance, a cube can have dimensions named “Accounts”, “Versions” and “Time”, and a number of other dimensions with other names. Each dimension comprises a list of members. For example, an “Organization” dimension in a cube comprises a list of departments and reporting entities for a company. The dimensions can also have a calculation structure that describes data aggregation, e.g. ‘East Region’=‘New York’ plus ‘Boston’, or a calculation structure that describes a more complex calculation, e.g. ‘Benefits’=10% of ‘Salaries’. It will be appreciated that calculations can also be different for each company.
• In the context of the present description, data is stored in an OLAP database as a single numerical value for each dimension combination. For example, if the dimensions are ‘Time’, ‘Accounts’, ‘Version’ and ‘Organization’, each of which has a member called ‘Jan08’, ‘Salaries’, ‘Plan’ and ‘Boston’ respectively, then one numeric value is stored for this combination of members. Similarly, a different number is stored in the database for ‘Feb08’, ‘Salaries’, ‘Plan’ and ‘Boston’.
• Typically, data is accessed (i.e. imported) in an OLAP database at a detailed level, for example, using the ‘Time’, ‘Accounts’, ‘Version’ and ‘Organization’ dimensions (e.g. ‘Jan08’, ‘Salaries’, ‘Plan’ and ‘Boston’). The data is then processed and reported at an aggregated level to provide historical information, for example, according to the dimensions, ‘Total Year’, ‘Total Expenses’, ‘Plan’ and ‘Total Company’.
• As will be described in more detail below, the present invention comprises embodiments of a system and method for accessing data in an OLAP database or cube, configuring operations (i.e. data processes) to process the data, and configuring manipulations involving the data.
• In the context of the present description, a process generally refers to data manipulation operations, and is referred to as “processes” or “data processes”. A typical process involves collecting data within a cube, performing an operation on it (e.g. an allocation, averaging or increasing/decreasing the amounts) and then storing data back in the cube. As will be described in more detail below, the present invention according to one aspect provides a structured approach and generalized interface configured for performing operations, such as, data collection, aggregation and storage, and combinations thereof, according to a variety of customer needs without the need for customization. According to a further aspect, the capability to handle exception conditions or customer specific operations is provided. Process in the context of the present description will also refer to a computer-implemented process (i.e. a computer function or software configuration) to execute an algorithm or perform other computer-implemented or configured operations or functions.
• In accordance with embodiments of the present invention a system and techniques (e.g. computer-implemented processes) are described in more detail below for accessing data in an OLAP database and configuring processes for manipulating and processing the data.
• Reference is made toFIG. 1, which shows in diagrammatic form an exemplary operating environment and configuration for a system and processes according to embodiments of the present invention. The operating environment according to an embodiment and indicated generally byreference100 comprises a client/server configuration. As shown, one or more clients110, indicated individually byreferences110a,110b,110c, . . .110n, access a server indicated byreference120, for example, through anetwork130. Thenetwork130 may comprise a local area network (LAN), a wide area network (WAN), the Internet or any combination thereof. As shown theserver120 interfaces with adatabase140. According to an embodiment, thedatabase140 is configured as an OLAP database and comprises a number of cubes142, indicated individually byreferences142a,142b,142c,142d,142e, . . . . The cubes142 are configured with dimensions and members as described above and in further detail below.
• According to an embodiment, thesystem100 includes a storage module indicated generally byreference134. Thestorage module134 is configured to store data process definitions, for example, as defined by a user. According to an embodiment, thestorage module134 is implemented using a relational data structure or configuration.
• As shown inFIG. 1, theserver120 is configured with an application indicated generally byreference122. According to an embodiment, theapplication122 comprises aclient interface module124 and acalculation engine module126.
• Theclient interface module124 is configured to provide an interface with the client machines110. According to an embodiment, theclient interface module124 is implemented with a user interface or GUI (Graphical User Interface) which runs on each of the client machines110 as indicated generally byreference112. According to an embodiment, theclient interface module124 and theuser interface112 comprise logic and processes configured to provide a user with the capability to specify a processing request for data in thedatabase140, i.e. a process for querying structural component(s) associate with one of the cubes. According to an embodiment, theapplication122 includes a module for storing processes specified by a user in the database, for example, in thestorage module134.
• Thecalculation engine module126 comprises a computer-implemented process(es) or function(s) that runs on theserver120 and performs manipulation of data in the cube142 according to a specification, i.e. a data process specified and provided by the user through theuser interface112. According to an embodiment, the execution of a data process is independent of the specification of the data process. For example, a data process can be executed multiple times and the execution of a data process can be scheduled to run at any time. According to an embodiment, the calculation engine is configured to execute process definition(s) retrieved or returned from thestorage module134.
• For example, the system and method according to the present invention provides the capability for accessing and/or manipulating data in an OLAP database in order to generate information for planning and reporting purposes. Typical examples include the following:
• • for each product, calculate monthly 2009 planned unit sales to be 10% greater than the monthly average for January thru September of 2008
  • for each product, calculate monthly material unit costs in 2009 to be 15% greater than the average in Quarter 3 of 2008
  • for a new product, the 2009 price for customers in the Eastern US is $100; in the West it is $110
  • for the optimistic scenario, increase the planned units sold by 100,000 for the whole of 2009, preserving the seasonality and the spread across branches.
  • for each month, take the total actual costs of the IT department and allocate them to lines of business based on number of computers in each department. Create a corresponding reversing entry in the IT department
  • in a reforecast, assume costs for July 2009 to December 2009 will be the same as in the budget, except in the Atlanta branch where they will be $100,000 less than budget.
• The functionality, logic and processes associated with theclient interface module124 and the user interfaces110 are described in more detail below according to embodiments of the invention. Embodiments of processing modules and functionality of thecalculation engine module126 are also described in more detail below.
• In the context of the processes and operations associated with theapplication122, i.e. theclient interface124 and thecalculation engine126, “Common Dimensions” are defined as dimensions within which data is not manipulated. The selected members of Common Dimensions determine the member combinations for which data manipulation will take place. For example, if the only Common Dimensions are Time and Products and the selected members are “January; February; March” and “Widgets; Grommets” respectively, then data manipulation will take place for each of the 6 combinations “January, Widgets”, “February, Widgets”, “March, Widgets”, “January, Grommets”, “February, Grommets” and “March, Grommets”.
• Source/target dimensions are dimensions within which data is manipulated. The selected source members of Source/Target Dimensions determine the member combinations for which data will be read from the cube. Selected Source dimension members can be calculated, for example, data can be copied from “Total Company” even if Total Company” is the aggregation of many departments. The selected target members of Source/Target Dimensions determine the member combinations for which data will be written back to the cube. Selected Target dimension members must be editable, i.e. leaf members, or non-calculated members into which data can be stored. In the context of the present description, a Source/Target dimension may be referred to as either a Source Dimension or a Target Dimension. Target Dimensions may be further subdivided into Time Target Dimensions and Non-Time Target Dimensions. If Time is a Target Dimension, the Time Target Dimension is the Time Dimension; otherwise it is the NULL dimension. The Non-Time Target Dimension comprises all Target Dimension except the Time Target Dimension.
• In accordance with this convention or notation, the address of a data cell or tuple comprises one of the following:
• • (1) a “Common Dimension” member combination and a “Source Dimension” member combination;
  • (2) a “Common Dimension” member combination and a “Target Dimension” member combination;
  • (3) a “Common Dimension” member combination, a “Time Target Dimension” member combination (i.e. either NULL or a single member of the Time Dimension) and a “Non-Time Target Dimension” member combination;
  • (4) a “Common Dimension” member combination when all dimensions are Common Dimensions, for example, when the operation being performed is “Storing single data value”.
• The configuration and operation of thecalculation engine126 and thesystem100 is now described in further detail with reference to the user interface depicted inFIGS. 2 to 6.
• According to an embodiment, theuser interface112 comprises five screens: aGeneral screen200 depicted inFIG. 2, a Common Dimensions screen300 depicted inFIG. 3, a Source/Target Members screen400 depicted inFIG. 4, aData Transformation screen500 as depicted inFIG. 5, and aProcessing Options screen600 as depicted inFIG. 6. As shown each of the screens includes five tabs: a “General”tab210, a “Common Dimensions”tab220, a “Source/Target Members”tab230, a “Data Transformation”tab240, and a “Processing Options”tab250. The screens are configured or implemented to provide a user with the capability to specify a process, i.e. a process for processing data in the database. The tabs allow a user to switch or move between screens and the layouts of certain screens will change depending on the options selected in the other tabs, as will be described in more detail below.
• TheGeneral screen200 is depicted inFIG. 2 according to an embodiment. TheGeneral screen200 is configured to provide a user with the capability to specify a cube142 (FIG. 1) in the database140 (FIG. 1) on which a data process is to be performed or executed. As shown inFIG. 2, theGeneral screen200 includes an “Operate on”panel260 for specifying the cube. Themain screen200 also includes an “Options” panel indicated byreference270. TheOptions panel270 is configured to allow a user to “Store or allocate based on existing data”272, store a user specifiedvalue274, or allocate a specifiedvalue276. The Store or allocateoption272 is configured to read the data to be processed read from the cube. Thestore option274 is configured to store a value entered inbox275 by the user at process definition time. The allocateoption276 is configured to allocate a value entered by the user inbox277 by the user during the definition of the data process.
• TheCommon Dimensions screen300 is depicted inFIG. 3 according to an embodiment. TheCommon Dimensions screen300 is configured to provide a user with the capability to select Common Dimensions for a process that will be executed by thecalculation engine126. TheCommon Dimensions screen300 is also configured to provide the capability to select “members” of the Common Dimensions for the process. As shown inFIG. 3 and according to an embodiment, cube dimensions indicated byreference310 are displayed and the user selects a dimension by clicking the associated checkbox. The members associated with a Common Dimension are displayed on thescreen300 as indicated byreference320. Once a Common Dimension for the cube is selected, the user is able to select one or more of the members for the selected Common Dimension. Members for unchecked Common Dimensions (i.e. non-Common Dimensions) cannot be selected. According to another aspect, at least one member must be selected in a Common Dimension for a data process to be run by the calculation engine. According to another aspect, if the data process comprises the “Store the following value” operation, then thescreen300 is configured to select all of the Common Dimensions and the checkboxes cannot be edited.
• The Source/Target Members screen400 according to an embodiment is shown inFIG. 4. The Source/Target Members screen400 is configured to provide a user with the capability to select Source members and/or Target members for non-Common dimensions in a cube. According to an embodiment, the Source/Target Members screen400 comprises a Source Data panel410 and aTarget Members panel420. The Source Data panel410 displays non-Common (Source) Dimensions, for example, “Versions” and “Time”, as indicated by reference412. TheTarget Members panel420 displays the Members for the selected non-Common Dimension, as indicated byreference414. According to an aspect, at least one member must be selected in each Source Dimension for a data process to be run by the calculation engine. It will be appreciated that the selected members for the Source Dimensions specify the cells in the cube (i.e. tuples) from which data is read. According to another aspect, if the data process comprises a “Store the following value” operation or an “Allocate the following value” operation, then the Source Data panel410 is deactivated on thescreen400.
• Referring still toFIG. 4, theTarget Members panel420 provides the user with the capability to select Target Dimension members from each non-Common Dimension. TheTarget Members panel420 displays non-Common (Target) Dimensions, for example, “Versions” and “Time”, as indicated byreference422. TheTarget Members panel420 displays the Member for the selected non-Common Dimension, as indicated byreference424. If the Target Dimension is “Accounts” or “Versions”, then a single member can be selected. For other dimensions, thescreen400 is configured to allow single or multiple target members to be selected by the user. The selected members for the Target Dimensions specify the cells in the cube (i.e. tuples) to which data is written. According to another aspect, if the data process comprises a “Store the following value” operation, then theTarget Members panel420 is deactivated on thescreen400.
• TheData Transformation screen500 according to an embodiment is shown inFIG. 5A. TheData Transformation screen500 is configured to provide a user with the capability to specify how values read from the cube are aggregated, how values from the cube are manipulated, and/or how values are allocated back to the cube. As shown inFIGS. 5A and 5B, theData Transformation screen500 comprises a “Data calculation options”panel510, a “Time Spread”panel530, and a “Dimension spread” panel550.
• As shown inFIG. 5A, the Datacalculation options panel510 is configured for a “Source data aggregation option” indicated by512. This option specifies how data is to be aggregated from multiple Source Dimension member combinations. According to an embodiment, a drop-down list indicated byreference514 is provided and configured to allow the user to select from “Aggregate”, “Average including empty values”, “Average excluding empty values” and “Copy between time members” based on the following conditions being true:
• • time is a non-Common Dimension in the cube
  • the number (#) of Time source members is the same as the number (#) of Time target members
  • the Time source members comprise contiguous leaf members
  • the Time target members comprise contiguous leaf members
  • one Source Dimension member is selected for all non-Common dimensions other than Time
  • one Target Dimension member is selected for all non-Common dimensions other than Time
• According to a further aspect, theData Transformation screen500 is configured to activate/display the Sourcedata aggregation option512 based on the following conditions being true: the data process comprises the “Storing/Allocating Data Present in the Cube” operation, and there is more than one member selected from at least one Source Dimension.
• According to another aspect, the Datacalculation options panel510 includes a “Delete data from source” option as indicated by reference516 inFIG. 5A. The Delete data from source option516 allows a user to specify whether source data is to be deleted from the cube. TheData Transformation screen500 is configured to activate/display the “Delete data from source” option if the operation comprises “Storing/Allocating Data Present in the Cube”.
• According to another aspect, the Datacalculation options panel510 includes a “Generate contra account entry” option as indicated byreference518 inFIG. 5B. The Generate contraaccount entry option518 allows a user to specify whether data being allocated is to be used in a contra account, and if yes, in which account. TheData Transformation screen500 is configured to activate/display the “Generate contra account entry”option518 based on the following conditions being true:
• • the data process comprises the“Storing/Allocating Data Present in the Cube” operation
  • Accounts comprise a non-Common Dimension
  • at least one dimension, other than Versions and Accounts, comprises a non-Common Dimension
  • only one Source dimension member is selected for the non-Common Dimensions
• According to another aspect, the Datacalculation options panel510 includes an “Apply the following transformation to the source data” option as indicated byreference520 inFIG. 5A. The Apply the following transformation to thesource data option520 allows a user to specify how data is to be adjusted before being written to the cube. The options may be configured in a drop-down list521 and comprise the following options:
• • “None”
  • “Increase by Percentage”
  • “Decrease by Percentage”
  • “Increase by Absolute Amount”
  • “Decrease by Absolute Amount”
  • “Multiply by Amount”
• According to another aspect, the Datacalculation options panel510 includes a “Target data write” option as indicated byreference522 inFIGS. 5A and 5B. The Target data writeoption522 allows a user to specify how data is to be written to a cube. The Target data write options may be configured in a drop-downlist523 and comprise the following options:
• • “Overwrite Existing Data”
  • “Add to Existing Data”
  • “Subtract from Existing Data”
• The Time spread panel indicated byreference530 inFIGS. 5A and 5B is configured to allow a user to specify how data is to be allocated across the Time Target dimension. According to an embodiment, the Time spreadpanel530 allows data to be allocated according to the following options:
• • “Store value to leaf members” indicated by532
  • “Spread based on existing data” indicated by534
  • “Spread based on data in a member property dimension” indicated by536
  • “Spread based on data in a different member combination” indicated by538
  • “Spread evenly” indicated by540
• According to an embodiment, theData Transformation screen500 is configured to display/activate the Time spreadpanel530 when the following conditions are true:
• • the operation is not a “Store the following value” operation
  • “Time” is non-Common dimension
  • there is more than one target member selected from the Time dimension
  • the option selected for “Source Data Aggregation” is not “Copy between time members”
• As shown inFIG. 5A, the “Spread based on data in a member property dimension”option536 includes a drop-down list537 for specifying additional parameters such as “Start Date”. According to another aspect, the Time spreadpanel530 is configured to displayinput boxes539 for the cube dimensions, i.e. “Account”, “Version” and “Time Periods”. The cube dimensions are associated with the Spread based on data in a differentmember combination option538. The default selected member for each of the cube dimensions is “Same as Target”.
• The Dimension spread panel indicated by reference550 inFIG. 5B is configured to allow a user to specify how data is to be allocated across non-Time Target dimensions. According to an embodiment, the Dimension spread panel550 allows data to be allocated according to the following options:
• • “Store value to leaf members with no spread” indicated by552
  • “Spread based on existing data” indicated by554
  • “Spread based on data in a member property dimension” indicated by556
  • “Spread based on data in a different member combination” indicated by558
  • “Spread evenly” indicated by560
• According to an embodiment, theData Transformation screen500 is configured to display/activate the Dimension spread panel550 when the following conditions are true:
• • the operation is not a “Store the following value” operation
  • there is at least one non-Common Dimension other than the cube dimensions “Time”, “Versions” and “Accounts”
  • there is more than one target member selected from at least one non-Common dimension other Time, Versions and Accounts
• According to another aspect, the Dimension spread panel550 is configured to displayinput boxes559 for the cube dimensions, i.e. “Account”, “Version” and “Time Periods” for the case of the “Spread Based on the existing data pattern”option558. According to an embodiment, the cube dimensions, except the dimensions associated with selected multiple Target members, are displayed and the user can select a single member from each. The default selected member for each of the cube dimensions is “Same as Target”.
• TheProcessing Options screen600 is accessed by theProcessing Options tab250 and an exemplary implementation according to an embodiment is shown inFIG. 6. TheProcessing Options screen600 is configured to provide a user with the capability to specify how the data process is to handle exception conditions. As shown inFIG. 6, theProcessing Options screen600 comprises a “Spread based on zero”panel610, a “Non-editable member combinations”panel620, and a “Details to log”panel630.
• As shown inFIG. 6, the “Spread based on zero”panel610 comprises a “Time Spread Invalid Value Handling” condition indicated byreference612. According to an embodiment, the Time Spread Invalid Value Handling includes a drop-downlist box614 with the following options:
• • “Spread evenly with no warning”
  • “Spread evenly, but generate a warning”
  • “Skip this member combination with no warning”
  • “Skip this member combination, but generate a warning” as shown in thelist box614 inFIG. 6
  • “Abort the process”
• Referring again toFIG. 6, the “Spread based on zero”panel610 also includes a “Dimension Spread Invalid Value Handling” condition indicated byreference616. According to an embodiment, the Time Spread Invalid Value Handling includes a drop-down list box618 with the following options:
• • “Spread evenly with no warning”
  • “Spread evenly, but generate a warning”
  • “Skip this member combination with no warning”
  • “Skip this member combination, but generate a warning” as shown in the list box618 inFIG. 6
  • “Abort the process”
• As shown inFIG. 6, the “Non-editable member combinations”panel620 comprises a “When a target member combination that is non-editable is encountered, how should it be handled” option indicated byreference622. TheNon-editable member panel620 is configured to allow a user to specify what processing occurs if data is to be written to dimension member combinations that are not editable for one or more reasons. According to an embodiment, theNon-editable member panel620 includes a drop-downlist box624 with the following options:
• • “Skip the member combination, but generate a warning” as indicated in thelist box624 inFIG. 6
  • “Skip the member combination with no warning”
  • “Abort the process”
• The “Details to log”panel630 is configured to provide user selectable reporting options as indicated byreference632. According to an embodiment, a drop-downlist box634 is provided to list reporting options, for example, including Minimal (as shown), Moderate, Maximum or Full.
• Reference will next be made toFIGS. 7 to 19, which further describe the processes, logic and operations associated with the user/client interfaces112,124 (FIG. 1) and/or thecalculation engine126, according to embodiments of the present invention.
• The data flow in accordance with an embodiment may be generalized as follows:
• • a data process can be executed for multiple combinations of entities. These entities are based on “common” dimensions. For example, the dimensions “Products” and “Customers” comprise common dimensions, and the process is run for each of 10,000 products and for each of 1,000 customers, for a total of 10,000,000 times.
• for each combination of Common Dimensions, the following steps occur:
• • the data is aggregated or averaged from multiple cells in the cube being calculated (based on “Source” members of each non-Common dimension). For example, the average price across all weeks in a quarter, or the total costs for all departments can be calculated. Alternatively, this value can be specified as a fixed value if the process does not involve reading cube data.
  • the calculated value can be manipulated further. For example, the average price can be increased by 5%.
  • the value is then either stored in multiple cells in the cube or allocated (spread) across multiple cells (based on “Target” members of each non-Common dimension). If the data is allocated, an allocation method is specified; the data can be spread evenly, or based on data that already exists in the cube. For example, in order to forecast seasonality, a sales forecast can be spread across months based on the previous year's sales.
• Thecalculation engine126 is configured to read data from cells (i.e. tuples) in the cube, and the cells are selected based on combinations of the selected Common Dimension members and the selected source members of Source/Target Dimensions, for example, using the logic as described for the user interface screens. Thecalculation engine126 is configured to write data to cells (i.e. tuples) based on combinations of the Common Dimension members and target members of Source/Target Dimensions, which are selected, for example, through the user interface screens as described above.
• According to an embodiment, thecalculation engine126 is configured to execute three types of operations: (1) “Store or allocate based on existing data”; (2) “Store single data value”; and (3) “Allocate single data value”. For the Store or allocate based on existing data operation, thecalculation engine126 includes a process or function configured to read from the cube and aggregate, and optionally, average to derive a single data value. The operations “Store single data value” and “Allocate single data value” represent special cases, when the data that is the source of a Process is not present in the cube. For the Store singe data value operation, thecalculation engine126 includes a process or function configured to populate the cube with identical values, e.g. “Product X prices are $100 for all months in all markets”. For the Allocate single data value operation, thecalculation engine126 is configured to allocate a single value across many dimensions, e.g. “Adjust the plan by decreasing planned Total Company Telephone Expenses to $1,000,000 and spread this across departments based on the existing plan”.
• In the context of the present description, Common Dimensions comprise a “looping” mechanism that allows data to be read from the cube and written to the cube independently for each combination of selected members from the Common Dimensions.
• For each of these combinations, thecalculation engine126 is configured as follows:
• • (1) for reading data from the cube, thecalculation engine126 is configured to read multiple values from the combinations of all selected source members of Source/Target Dimensions; the values can be either aggregated or averaged, the result of which is one data value for each combination of selected Common Dimension members;
  • (2) read data options—thecalculation engine126 is configured to optionally delete data thus read from all combinations of all selected source members of Source/Target Dimensions;
  • (3) specified data values—thecalculation engine126 is configured to manipulate data on an individual basis; for example, thecalculation engine126 includes a process for “Storing single data value”, and a process “Allocating single data value”); in these cases, the same data value is used for all combinations of selected Common Dimension members;
  • (4) data transformations—thecalculation engine126 is configured to transform a single data value that is, for example, the result of collecting data from the cube, or that, for example, has been entered as a single value; according to another aspect, thecalculation engine126 is configured to add and/or subtract absolute or percentage amounts to the data value, or multiply the data value (by a factor);
  • (5) writing data to the cube—thecalculation engine126 is configured to write the data value to the combinations of all selected target members of Source/Target Dimensions. According to a further aspect, the single data value is spread (i.e. allocated) across these combinations or stored in each combination;
  • (6) allocations—thecalculation engine126 is configured to allocate data to target dimension members; according to another aspect, thecalculation engine126 is configured to allocate or spread data to the combinations of selected target members of Source/Target Dimensions as follows (for example, as described above the with reference to the user interface112):
    • “Store value to leaf members” (i.e. copy, don't allocate)
    • “Spread Based on Existing Data”
    • “Spread Based on Data in a dimension Member Property”
    • “Spread Based on data in a different member combination”
    • “Spread Evenly”
    • Data allocation for the Time Dimension is treated differently as described in more detail below. Data allocation according to the “Spread Based on data in a different member combination” is treated as an exception to the methods of addressing cells, as described in more detail below.
  • (7) write data options—thecalculation engine126 is configured to write allocated data to the cube according to the following options:
    • “Overwrite Existing Data”
    • “Add to Existing Data
    • “Subtract from Existing Data
• According to another aspect, thecalculation engine126 is configured to optionally adjust data in the selected Source dimension members. It will be appreciated that this function allows adjustments to be made, for example, for financial reporting purposes when overheads are allocated between business entities, as described in more detail with respect to “Contra Accounts”.
• Reference is now made toFIG. 7, which shows an embodiment of a process or processing algorithm for the calculation engine denoted byreference700. Theprocessing algorithm700 is implemented to calculate or execute the data processes associated with the cube. According to an embodiment, theprocess700 is called or invoked as indicated by reference701. According to one aspect, the processing algorithm treats all dimensions as equal. According to another aspect, dimensions are separated into two types of dimensions: (1) common dimensions; and (2) source/target dimensions.
• As shown inFIG. 7, adecision step710 is executed to determine the type of “Source data aggregation” operation to be executed. The Source data aggregation operation can be specified by the user according to one or more options, for example, using the Data Transformation Tab operation, as described above with reference toFIG. 5(a). If the Source data aggregation operation comprises a “Copy between time members” operation, then a “Copy between time members” process is executed as indicated by712. The Copy between time members process executes a process to copy between time members as described in more detail below with reference toFIG. 17. Otherwise, a looping operation through the associated or defined Common Dimension Combinations is executed as indicated byreference720. For example, if Product is a Common Dimension and there are 10 members of Product selected, then the process will be calculated for each of the selected members. The number of cells affected in an operation (such as reading or writing data) is determined by the number of members selected in each cube dimension. The number of cells affected is the product of the numbers of members selected in all cube dimensions. As shown inFIG. 7, a check is made in730 to determine if all the Common Dimension Combinations have been considered. If not, the loop process is repeated for the next Common Dimension Combination as indicated by732.
• As shown inFIG. 7, a process is executed in722 to calculate “Value to Process” for the common dimension combination. The Value to Process comprises a process that is configured to read cube data and aggregate the data or calculate an average value. An embodiment of a process to calculate “Value to Process” is described in more detail below with reference toFIG. 8. Next, a process to adjust “Value to Process” is executed as indicted byreference724. The Adjust Value to Process comprises a process configured to calculate adjustments to data read from the cube. An embodiment of a process for adjusting “Value to Process” is described in more detail below with reference toFIG. 9. Next as indicated byreference726, a check is made to determine if the operation involves storing a single data value. If yes, the single data value is assigned to “Value to Store” as indicated byreference736, and process configured to Store Data in the Cube is called or invoked as indicated byreference738. An embodiment of a process to store data in the cube is described in more detail below with reference toFIG. 16. If the operation does not involve a single data value (i.e. as determined in726), then a process configured to “Write Data to Cube” is called or invoked as indicated byreference728. The write data to cube process manages the allocation of data across the Time Dimension. An embodiment of write data to cube process is described in more detail below with reference toFIG. 10. If the last common dimension combination has been considered (i.e. as determined in730), then post processing may be initiated or invoked as indicated byreference734. According to an embodiment, the post processing comprises execution of a process configured to manage deletion of source data and/or generation of contra account entries, as described in more detail below with reference toFIG. 18. Thecalculation engine126, and its associated processes, terminate as indicated byreference740.
• Reference is next made toFIG. 8, which shows in flowchart form an embodiment of a process to calculate the “Value to Process”. The process is indicated generally byreference800 and was called or invoked as indicated by reference722 (FIG. 7). The process for calculating value to process comprises first determining if the specified data process comprises a “storing/allocating data present in the cube” operation as indicated byreference810. If no, then the “Value to Process” is set to the entered data value, and theprocess800 is terminated or ended as indicated byreference860. If the process comprises a “storing/allocating data present in the cube” operation (decision block810), then the “Value to Process” parameter is set to zero as indicated byreference812. Next a looping operation through the associated or defined Source Dimension Combinations is executed as indicated byreference820. For example, if a Source Dimension has 12 members and 10 members are selected, then the process will be calculated for each of the selected members. The number of cells affected in an operation (such as reading or writing data) is determined by the number of members selected in each cube dimension. The number of cells affected is the product of the numbers of members selected in all cube dimensions. As shown inFIG. 8, a check is made in828 to determine if all the Source Dimension Combinations have been considered.
• As shown inFIG. 8, the first step in the looping operation involves reading a “Cell Data Value” for the Common Dimension Combination/Source Dimension Combination, as indicated byreference822. Next in decision block824 a check is made for a missing data value. If a data value is missing, then the next step involves incrementing the parameter “# Data Cells Read” by one (1), as indicated byreference825. If a data value is not missing (decision block824), then the next step comprises incrementing the parameter “Value to Process” by the “Cell Data Value” and incrementing by one (1) the parameter “# Non-Missing Data Cells Read” and the parameter “# Data Cells Read”, as indicated byreference826. If this is the “Last Source Dimension Combination” (as determined in step828), then a check is made indecision block840 to determine if the “Source Data Aggregation Option” is the “Aggregate”, if yes then theprocess800 is terminated or ended as indicated byreference860. If no, then a check is made indecision block842 to determine if the “Source Data Aggregation Option” is equal to the calculated “Average including empty values”. If no, then the “Value to Process” is divided by the number of Non-Missing Data Cells Read” instep846, and then theprocess800 is terminated instep860. If the “Source Data Aggregation Option” is equal to the calculated “Average including empty values” (as determined in decision block842), the “Value to Process” is divided by the number of “Data Cells Read” instep844, and then theprocess800 is terminated instep860.
• Reference is next made toFIG. 9, which shows in flowchart form an embodiment of a process, i.e. a software process or processor configured to adjust the “value to process”. The process is indicated generally byreference900 and is called or invoked as indicated by reference724 (FIG. 7). The process for adjusting the “value to process”900 comprises applying one or more transformations to “Source Data”. A check is made instep910 to determine if the first transformation comprises increasing the source data by a percentage. If no, then the next transformation is determined instep920. If yes, then the “Value to Process”, i.e. the source data, is increased by a specified percentage, as indicated byreference912. Next a check is made instep920 to determine if the transformation comprises decreasing the source data by a percentage. If no, then the next transformation is determined instep930. If yes, then the “Value to Process”, i.e. the source data, is decreased by a specified percentage, as indicated byreference922. Next a check is made instep930 to determine if the transformation comprises increasing the source data by an absolute amount. If no, then the next transformation is determined instep940. If yes, then the “Value to Process”, i.e. the source data, is increased by a specified amount, as indicated byreference932. Next a check is made instep940 to determine if the transformation comprises decreasing the source data by an absolute amount. If no, then the adjust sourcedata value process900 ends or terminates as indicated instep950. If yes, then the “Value to Process”, i.e. the source data, is decreased by a specified amount, as indicated byreference942, and theprocess900 terminates instep950.
• Reference is next made toFIG. 10, which shows in flowchart form an embodiment of a process, i.e. a software process or processor configured to write or allocate data to a cube. The process is indicated generally byreference1000 and is called or invoked as indicated by reference728 (FIG. 7). According to an embodiment, the process according to the present invention treats time as a special dimension for the purposes of allocating, i.e. writing, data to the cube. If time is a Target Dimension with multiple Target Dimensions being selected, then according to an embodiment, data is allocated across the time dimension before being allocated across other dimensions. According to this aspect, the time dimension has a different allocation method or process than the other target dimensions.
• As shown inFIG. 10, theprocess1000 comprises a number of operations or steps for writing data to a cube. As shown, the first step comprises determining if the time parameter is a “Common Dimension”, as indicated bydecision block1010. If yes, then the data to write to the cube, i.e. “Value to Allocate”, is based on the “Value to Process”, as indicated byreference1060, and because “Time” is a “Common Dimension”, the “Value to Process” is allocated across the non-Time target dimension for the cube instep1062, and the write data tocube process1000 ends as indicated bystep1070. A process for allocating across non-time target dimensions according to an embodiment is described in more detail below with reference toFIG. 13.
• If Time is not a Common Dimension (as determined in decision block1010), then a check is made to determine if the number of Time Target Members is greater than one, as indicated bydecision block1020. If no, then the data to write to the cube, i.e. “Value to Allocate”, is based on the “Value to Process”, as indicated byreference1060, and because “Time” is a “Common Dimension”, the “Value to Process” is allocated across the non-Time target dimension for the cube instep1062. The process for writing data tocube1000 ends as indicated bystep1070. If yes (as determined in decision block1020), then next a determination is made indecision block1030 to determine if the “Time Spread Option” is set to “Store value to leaf members”. If no, then a process to calculate time allocation parameters is called as indicated bystep1032, and described in more detail below with reference toFIG. 11. If the Time Spread Option is set to Store value to leaf members (decision block1030), then the process loops through the Time Target Dimension Combinations as indicated generally byreference1040. As indicated bydecision block1042, a check is made to determine if the Time Spread Option is set to Store value to leaf members. If yes, then the Value to Allocate (i.e. the data to write to the cube) is set to the “Value to Process” as indicated byreference1043, and a process to allocate across non-time target dimensions is called instep1046. An embodiment of a process to allocate across non-time target dimensions is described in more detail below with reference toFIG. 13.
• As shown inFIG. 10, if the time spread option is not set to store value to leaf members (as determined in decision block1042), then a process to calculate Time Allocated “Value to Allocate” is called instep1044. An embodiment of a process to calculate Time Allocated “Value to Allocate” is described in more detail below with reference toFIG. 12. Next, the process to allocate across non-time target dimensions is called instep1046. And then instep1048, a check is made to determine if the last Time Target Dimension Combination has been considered. If no, then the next Time Target Dimension Combination is determined instep1050 and the looping operation (as indicated in block1040) is repeated. Otherwise, the process for writing data to thecube1000 ends as indicated byreference1070.
• Reference is next made toFIGS. 11A and 11B, which show in flowchart form an embodiment of a process, i.e. a software process or processor configured to calculate time allocation parameters. The process is indicated generally byreference1100 and is called or invoked as indicated by reference1032 (FIG. 10). The process for calculating thetime allocation parameters1100 comprises initializing the following parameters: “Time Target Denominator”=0; “Time Non-Editable Values”=0; and “# Time Editable Values”=0, as indicated byreference1110. Next, theprocess1100 comprises looping through the Time Target Dimension Combination(s) as indicated generally by reference1120. As indicated bydecision block1122, a check is made to determine if the Time Member parameter is editable. If no, then theprocess1100 loops through Non-Time Target Dimension Combination (s0 as indicated byreference1160, as will be described in more detail below. If yes (as determined in decision block1122), then the next step comprises incrementing the parameter “# Time Editable Values”, as indicated byreference1124. Next, a determination is made instep1126 to determine if the “Time Spread Option” is set to “Spread Evenly”. If yes, then a check is made to determine if the all the Time Target Dimension Combinations have been considered, as indicated by reference1150. If no, then a check is made to determine if the “Time Spread Option” is set to the option “Based on Member Properties”, as indicated bydecision block1128. If no, then the process loops through Non-Time Target Dimension Combinations as indicated byreference1140 and described in more detail below. If yes, then theprocess1100 reads or inputs the “Member Property Value” associated with the Time Target Dimension Combination, as indicated by reference1130. Next, theprocess1100 increments the parameter “Time Target Denominator” by the value for the “Member Property Value”, as indicated by reference1132. If there are still Time Target Dimension Combinations to loop through as determined in step1150, then the next Time Target Dimension Combination is selected, as indicated by reference1152, and the looping process (step1120) is repeated. Otherwise, the process for calculatingtime allocation parameters1100 terminates or ends, as indicated byreference1170, and control returns to the calling process or function.
• Referring again toFIGS. 11A and 11B, if the Time Member cannot be edited (as determined in decision block1122), then theprocess1100 executes the looping operation through the Non-Time Target Dimension Combinations as indicated byreference1160. As indicated byreference1162, the looping operation comprises reading or inputting the “Cell Data Value” for the Common Dimension Combination/Target Dimension Combination. Next, as indicated by reference1164, the “Time Non-Editable Values” is incremented by the Cell Data Value (read in step1162). Next in step1166, a check is made to determine if the last Non-Time Target Dimension Combination has been considered. If no, then the next Non-Time Target Dimension Combination is determined in step1168 and the looping operation (as indicated in block1160) is repeated. Otherwise, the process the moves to step1150 as described above.
• Referring toFIGS. 11A and 11B, if the “Time Spread Option” is not set to “Based on Member Properties” (as determined in decision block1128), then theprocess1100 executes the looping operation through the Non-Time Target Dimension Combinations as indicated byreference1140. As indicated bydecision block1142, a check is made to determine if the parameter “Time Spread Option” is set to “Spread Based on Existing Data”. If no, then theprocess1100 stores data based on a different member combination. As indicated byreference1143, theprocess1100 is configured to read or input a “Cell Data Value” for a different Common Dimension Combination/Target Dimension Combination. Next and as indicated by reference1146, theprocess1100 increments the Time Target Denominator by the Cell Data Value (in this case the Cell Data Value read in step1143). Next instep1148, a check is made to determine if the last Non-Time Target Dimension Combination has been considered. If no, then the next Non-Time Target Dimension Combination is determined instep1149 and the operation (as indicated in block1142) is repeated. Otherwise, the process moves to step1150 as described above.
• Referring again toFIGS. 11A and 11B, if the “Time Spread Option” is set to “Spread Based on Existing Data” (as determined in decision block1142), then theprocess1100 is configured to read or input a “Cell Data Value” for the Common Dimension Combination/Target Dimension Combination, as indicated byreference1144. Next, theprocess1100 increments the Time Target Denominator by the Cell Data Value (in this case the Cell Data Value read in step1144), as indicated by reference1146. Next instep1148, a check is made to determine if the last Non-Time Target Dimension Combination has been considered. If no, then the next Non-Time Target Dimension Combination is determined instep1149 and the operation instep1142 is repeated as described above. Otherwise, the process moves to step1150 as described above.
• Reference is next made toFIG. 12, which shows in flowchart form an embodiment of a process, i.e. a software process or processor configured to calculate the time allocation for value to allocate. The process is indicated generally byreference1200 and is called or invoked as indicated by reference1044 (FIG. 10). The process for calculating the time allocation for value to allocate1200 comprises first determining if the Time Spread Option is set to “Spread Evenly” indecision block1210. If yes, then according to an embodiment, the “Value to Allocate” is calculated as follows,
• 
  Value to Allocate=(Value to Process−Time Non-Editable Values)/# Time Editable Values
• Next, the process for calculating time allocated for value to allocate1200 terminates or ends as indicated by reference1240, and control returns to the calling process or function.
• If no (as determined in decision block1210), then a check is made indecision block1212 to determine if the Time Spread Option is set to “Based on Member Properties”. If yes, then the next operation in theprocess1200 comprises reading or inputting the “Member Property Value” for the Time Target Dimension Member, as indicated byreference1214. Next and according to an embodiment, the Value to Allocate is calculated instep1216 as follows:
• 
  ValueToAllocate=(ValueToProcess−TimeNon-EditableValues)*MemberPropertyValue/TimeTargetDenominator
• Next, the process for calculating time allocated for value to allocate1200 terminates or ends as indicated by reference1240.
• If the Time Spread Option is not set to the Based on Member Properties (as determined in decision block1212), then a check is made indecision block1220 to determine if the Time Spread Option is to the “Spread Based on Existing Data” option. If yes, then the next operation in theprocess1200 comprises reading or inputting the “Cell Data Value” for the Common Dimension/Target Dimension Combination, as indicated byreference1222. Next and according to an embodiment, the Value to Allocate is calculated instep1224 as follows:
• 
  ValueToAllocate=(ValueToProcess−TimeNon-EditableValues)*CellDataValue/TimeTargetDenominator
• The process for calculating time allocated for value to allocate1200 then terminates or ends as indicated by reference1240.
• Referring again toFIG. 12, if the Time Spread Option is not set to Spread Based on Existing Data (as determined in decision block1220), then theprocess1200 operates to store (allocate) based on a different member combination. As indicated byreference1230, the next operation in theprocess1200 comprises reading or inputting the “Cell Data Value” for the Different Common Dimension/Target Dimension Combination. Next and according to an embodiment, the Value to Allocate is calculated instep1232 as follows:
• 
  ValueToAllocate=(ValueToProcess−TimeNon-EditableValues)*CellDataValue/TimeTargetDenominator
• Next, the process for calculating time allocated for value to allocate1200 terminates or ends as indicated by reference1240.
• Reference is next made toFIG. 13, which shows in flowchart form an embodiment of a process, i.e. a software process or processor configured to allocate data across non-time target dimensions. The process is indicated generally byreference1300 and is called or invoked as indicated byreference1046 or1062 (FIG. 10). The process for allocating data acrossnon-time target dimensions1300 comprises determining if the operation comprises “Storing a single data value” as indicated bydecision block1310. If the operation comprises storing a single data value (as determined in decision block1310), then the next operation in theprocess1300 comprises setting “Value to Store” to “Value to Allocate” as indicated byreference1350. If the operation is not set to “Storing single value data” (i.e. as determined in decision block1310), then theprocess1300 checks if the “Dimension Spread Option” is set to “Store value to leaf members” as indicated bydecision block1320. If yes, then the process performs the operation instep1350 as described above. Next theprocess1300 loops through the Non-Time Target Dimension Combination(s) as indicated byreference1352. The looping operation includes storing data in the cube as indicated byreference1354. A process or function configured to store data in a cube according to an embodiment is described in more detail below with reference toFIG. 16. A check is made instep1356 to determine if there are any other Non-time Target Dimension Combinations to consider, then the next Non-time Target Dimension Combination is selected, as indicated byreference1358, and the looping process (reference1352) is repeated. Otherwise, the process for allocating data to a cube acrossnon-time target dimensions1300 terminates or ends, as indicated byreference1360, and control returns to the calling process or function.
• Reference is next made toFIG. 16, which shows an embodiment of a process or processor configured to store data in a cube. The process for storing data in a cube is indicated generally byreference1600. As described above, the process for storing data in acube1600 is invoked or called, for example, by the process for allocating data across non-time target dimensions1300 (FIG. 13). As shown, the process for storing data in acube1600 first determines if the target data write option is set to “Overwrite Existing Data” as indicated bydecision block1610. If the option is set to overwrite, then the value to write parameter is set to the “Value to Store” as indicated byreference1611. The next step involves writing the data, i.e. the “Value to Write”, to the cube for the associated “Common Dimension Combination” or “Target Dimension Combination” as indicated byreference1620. If the target data write option is not set to overwrite existing data (for example, according to the settings under theData Transformation tab240 as described above inFIG. 5), theprocess1600 is configured to read “Old Cube Data” for the Common Dimension Combination which is concatenated with the Target Dimension Combination, as indicated byreference1612. Next indecision block1614, a check is performed to determine if the target data write option is set to “Add to Existing Data”. If the option is set, then the parameter “Value to Write” is set to the “Old Cube Data” plus the value for the parameter “Value to Store”, as indicated byreference1616. If the option is not set (as determined in step1614), then the parameter “Value to Write” is set to the “Old Cube Data” less the value for the parameter “Value to Store”, as indicated byreference1618. The next operation involves writing the data to the cube as indicated byreference1620 and described above. The process for storing data in acube1600 terminates or ends as indicated byreference1630, and control returns to the calling process or function.
• Referring back toFIG. 13, if the option is not set to “Storing value to leaf members” (as determined in decision block1320), then a check is made to determine if the “Dimension Spread Option” is set to option “Spread Evenly” as indicated bydecision block1330. If the option is set to “Spread Evenly” (for example, using the Data Transformation screen as described above with reference toFIG. 5), then theprocess1300 is configured to set the value to store to the “Value to Allocate” which is divided by the number of Non-time Target Dimension member Combinations as indicated byreference1331. Next, theprocess1300 performs the looping operation as indicated byreference1352 and described above. If the option is not set to “Spread Evenly” (as determined in decision block1330), then theprocess1300 is configured to calculate non-Time Allocation parameters as indicated byreference1332. According to an embodiment, a process or function is called instep1332 which is configured to calculate the non-Time Allocation parameters as described in more detail below with reference toFIG. 14.
• Reference is next made toFIGS. 14A and 14B, which show a process or processor configured for calculating non-time allocation parameters according to an embodiment of the invention and indicated generally byreference1400. As shown and indicated byreference1410, the following variables/parameters are set to zero (0): “non-Time Target Denominator”, “non-Time Non-Editable Values” and “# non-Time Editable Values”. Theprocess1400 comprises looping through the non-Time Target Dimension Combination(s) as indicated by reference1420. Theprocess1400 determines if the non-Time Member can be edited as indicated bydecision block1422. If no, theprocess1400 is configured to read or input the “Cell Data Value” for the Common Dimension/Target Dimension Combination as indicated byreference1450. Next, the non-Time non-editable value(s) are incremented by the “Cell Data Value”, as indicated byreference1452. A check is made to determine if there are any more non-Time Target Dimension Combinations to consider, as indicated byreference1440. If no, then the process for calculatingnon-time allocation parameters1400 terminates or ends as indicated by reference1470, and control is return to the calling process or function. If yes, then theprocess1400 considers the next non-Time Target Dimension Combination as indicated byreference1442 and the looping operation in step1420 is repeated.
• Referring again toFIGS. 14A and 14B, if the non-time member is editable (as determined in decision block1442), then theprocess1400 is configured to perform the following operations. Increment by one (1) the parameter, # of Time Editable Values, as indicated byreference1424, and check if the “Dimension Spread Option” is set to “Spread Evenly” as indicated by reference1426. If the option is not set to “Spread Evenly” (for example, using the Data Transformation screen as described above), then a check is made indecision block1428 to determine if the “Dimension Spread Option” is set to the “Based on Member Properties” option. If yes, then theprocess1400 is configured to read or input the data for the “Member Property Value” associated with the “Time Target Dimension Combination”, as indicated byreference1430. Next theprocess1400 increments the non-Time Target Denominator by the Member Property Value (read in step1430) as indicated byreference1432. Theprocess1400 then checks if this was the last non-Time Target Dimension Combination as indicated byreference1440. If yes, theprocess1400 ends (as indicated by reference1470) and control returns to the process for allocating acrossnon-time target dimensions1300 inFIG. 13. If no, then theprocess1400 considers the next non-Time Target Dimension Combination (as indicated by reference1442) and the looping operation (as indicated by reference1420) is repeated.
• Referring again toFIGS. 14A and 14B, if the Dimension Spread Option is not set to Based on Member Properties (step1428), then a check is made in decision block1460 to determine if the Dimension Spread Option is set to “Spread Based on Existing Data”. If yes, then theprocess1400 is configured to read or input the “Cell Data Value” from the cube for the Common Dimension Combination/Target Dimension Combination as indicated byreference1462. Theprocess1400 then increments the non-Time Target Denominator by the Cell Data Value, as indicated byreference1464. If the Dimension Spread Option is not set to Spread Based on Existing Data, then theprocess1400 is configured to store data based on a different member combination. As indicated by reference1461, theprocess1400 is configured to read the Cell Data Value for the Different Common Dimension Combination/Target Dimension Combination, and then the non-Time Target Denominator is incremented instep1464 as described above. If the last non-time target dimension combination has been considered, then theprocess1400 ends (as indicated by reference1470) and control returns to the process for allocating acrossnon-time target dimensions1300 inFIG. 13.
• According to an aspect, the process provides the capability to allocate data into non-editable (leaf) cells. For example, if a user wants to allocate a value across the 12 months in a year, but Jan, Feb and Mar contain historical data that is non-editable, then the process is configured to calculate the data values for the non-editable cells (i.e. Jan, Feb, Mar) and subtract the data values (i.e. the sum) from the values to be allocated to the editable cells.
• Referring back toFIG. 13, theprocess1300 next loops through the Non-Time Target Dimension Combinations as indicated byreference1334. The looping operation comprises calculating a non-time allocated value to store in the cube, as indicated byreference1336, and storing data in the cube as indicated byreference1338. A process or function configured to calculate a non-time allocated value for storing in the cube according to an embodiment is described in more detail below with reference toFIG. 15. After the non-time allocated value is determined instep1336, the process for storing data (i.e. the non-time allocated value) in the cube is executed as indicated byreference1338. An embodiment of the process for storing data in acube1600 is described above with reference toFIG. 16. A check is made instep1340 to determine if there are still Non-time Target Dimension Combinations to consider, then the next Non-time Target Dimension Combination is selected, as indicated byreference1342, and the looping process (step1334) is repeated. Otherwise, the process for allocating data to a cube acrossnon-time target dimensions1300 terminates or ends, as indicated byreference1360, and control returns to the calling process, i.e. the process for writing data to the cube1000 (FIG. 10).
• Reference is next made toFIG. 15, which shows an embodiment of a process (function) or processor configured to calculate a non-time allocated value, i.e. data, to store in the cube. The process is indicated generally byreference1500 and comprises determining if the Dimension Spread Option is set to “Spread Evenly”, as indicated byreference1510. If the option is set to Spread Evenly, thenprocess1500 determines the “Value to Allocate” (i.e. the data to write to the cube) as follows in step1511:
• 
  ValueToAllocate=(ValueToProcess−non-TimeNon-EditableValues)/# non-TimeEditableValues
• Next, the process for calculating the non-time allocated value tostore1500 terminates or ends as indicated byreference1540, and control returns to thecalling process1300 inFIG. 13.
• Referring again toFIG. 15, if the dimension spread is not set to spread evenly (as determined in decision block1510), then theprocess1500 is configured to check if the Dimension Spread option is set to the option “Based on Member Properties”, as indicated bydecision block1512. If yes, then theprocess1500 is configured to read the “Member Property Value” for the non-Time Target Dimension Member from the cube, as indicated byreference1514. Theprocess1500 then determines the “Value to Allocate” (i.e. the data to write to the cube) as follows in step1516:
• 
  ValueToAllocate=(ValueToProcess−non-TimeNon-EditableValues)*MemberPropertyValue/non-TimeTargetDenominator
• Next, the process for calculating the non-time allocated value tostore1500 terminates or ends as indicated byreference1540, and control returns to thecalling process1300 inFIG. 13.
• Referring again toFIG. 15, if the dimension spread is not set to based on member properties (as determined in decision block1512), then theprocess1500 is configured to check if the Dimension Spread option is set to the option “Spread Based on Existing Data”, as indicated bydecision block1520. If yes, then theprocess1500 is configured to read the “Cell Data Value” for the Common Dimension Combination/Target Dimension Combination from the cube, as indicated byreference1522. Theprocess1500 then determines the “Value to Allocate” (i.e. the data to write to the cube) as follows in step1524:
• 
  ValueToAllocate=(ValueToProcess−non-TimeNon-EditableValues)*CellDataValue/non-TimeTargetDenominator
• Next, the process for calculating the non-time allocated value tostore1500 terminates or ends as indicated byreference1540, and control returns to thecalling process1300 inFIG. 13.
• If the dimension spread option is not set to Spread Based on Existing Data (as determined in decision block1520), then theprocess1500 operates to calculate the non-time allocated value or data to store based on a different member combination. As indicated byreference1530, the next operation comprises reading or inputting the “Cell Data Value” for the Different Common Dimension/Target Dimension Combination. Next and according to an embodiment, the Value to Allocate is calculated instep1532 as follows:
• 
  ValueToAllocate=(ValueToProcess−NonTimeNon-EditableValues)*CellDataValue/NonTimeTargetDenominator
• Next, the process for calculating the non-time allocated value tostore1500 terminates or ends as indicated byreference1540, and control returns to thecalling process1300 inFIG. 13.
• It will be appreciated that according to an aspect, time is treated not the same as other dimensions. For instance, time has an implicit order of its members (e.g. January, February, March) whereas other dimensions have no such implicit order (e.g. Widgets, Grommets, Doodads). Because of this, when manipulating time-related data, the following statement makes sense; “Copy actual sales from January 2008 thru June 2008 into the plan for January 2009 thru June 2009”.
• Reference is next made toFIG. 17, which shows in flowchart form an embodiment of a process, i.e. a software process or processor configured to copy data between time members. The process is indicated generally byreference1700 and is called or invoked as indicated byreference712 inFIG. 7. According to an embodiment, the process is configured to handle multiple processes, i.e. one for each time period being processed. The process for copying betweentime members1700 comprises looping through the Common Dimension Combinations as indicated byreference1710. As shown, the loopingoperation1710 includes looping through the Source Dimension Combinations as indicated byreference1720. As shown, the loopingoperation1720 comprises reading or inputting the “Value to Process” for the Common Dimension/Source Dimension Combination instep1722. Next theprocess1700 calls the process for adjusting the value to process900 as described above with reference toFIG. 9. Next, theprocess1700 assigns the value to process (determined by the process900) to the parameter “Value to Store”, as indicated byreference1726. As indicated byreference1728, theprocess1700 then calls or invokes the process for storing data in the cube as described above with reference toFIG. 16. A check is made instep1730 to determine if the last source dimension combination has been considered. If there are more last source dimension combinations to process, then the next last source dimension combination is selected, as indicated byreference1732, and the looping process (step1720) is repeated. If all the last source dimension combinations have been considered, then a check is made instep1740 to determine if there are more common dimension combinations to consider. If yes, then the next common dimension combination is considered as indicated byreference1742 and the looping operation is repeated in1710, as described above. Otherwise, the process for copying data betweentime members1700 terminates or ends, as indicated byreference1750, and control returns to the calling process or function.
• It will be appreciated that according to an embodiment, the process for copying data betweentime members1700 operates to copy a single value between Time leaf members for each common dimension combination. The single members are selected for all Source and Target dimensions except for Time, which is a non-Common dimension. This requires cell addresses to be made from Common Dimension selected member combinations together with one Source dimension member for the source and one Target dimension member for the target of a single data value being copied. If multiple Time leaf members are selected, then the same number for both Source and Target dimensions are provided, and the Source members are contiguous and all Target members are contiguous. According to an aspect, addressing in the process is indexed through the selected Time members. For example, if the selected Source members are “Jan, Feb, Mar” and the selected Target members are “Jul, Aug, Sep” then data will be copied from Jan to Jul, Feb to Aug and Mar to Sep.
• Reference is next made toFIG. 18, which shows a post processing function or process according to an embodiment of the invention. The post processing process is indicated generally byreference1800. One of the operations configured for thepost processing process1800 is deleting source data. As indicated bydecision block1810, theprocess1800 checks if the delete data from source has been set to TRUE. If TRUE, then theprocess1800 is configured to loop through the common dimension combinations as indicated byreference1820. The loopingoperation1820 is configured to loop through the source dimension combinations as indicated byreference1822. As shown for the loopingoperation1822, theprocess1700 is configured to delete data for the common dimension combination and associated source dimension combination. Theprocess1800 checks instep1826 to determine if the last source dimension combination has been considered. If there are more last source dimension combination(s) to process, then the next last source dimension combination is selected, as indicated byreference1828, and the looping process (step1822) is repeated. If all the last source dimension combinations have been considered, then a check is made instep1830 to determine if there are more common dimension combinations to consider. If yes, then the next common dimension combination is considered as indicated byreference1832 and the looping operation is repeated in1820, as described above. If the last common dimension combination has been considered (as determined in step1830), then a check is made indecision block1840 to determine if the process is called or set to generate a contra account entry. If no, then thepost processing process1800 terminates or ends as indicated byreference1850. If yes, then theprocess1800 calls a process to generate a contra account entry as indicated byreference1842. An embodiment of a process to generate a contra account is described in more detail below with reference toFIG. 19. After the contra account entry is generated (step1842), the post processing process orfunction1800 terminates or ends, as indicated byreference1850.
• The generate contra account entry function is provided to handle an accounting requirement where allocated data needs to be reversed in the entity from which it is being allocated. For example, if total IT department costs in July are $500,000 then this amount can be allocated across lines of business based on the number of PCs used in each. The allocated amounts will be stored in a special allocation account. A reversing entry is made in the IT department so the net effect of this allocation at the total company level is zero. The reversing entry is stored in a Contra Account (which may be the same as the allocation account). According to an embodiment, the contra account functionality may be incorporated into a data process or function.
• Reference is next made toFIGS. 19A and 19B, which show an embodiment of a process to generate a contra entry. The process for generating a contra entry is indicated generally by reference1900 and according to embodiment is called or invoked by the post processing function1800 (FIG. 18). As shown, the generate contra entry process1900 comprises looping through the common dimensions as indicated by reference1910, looping through the source dimensions as indicated by reference1920, and looping through alternate common dimension combinations as indicated byreference1930.
• As shown inFIG. 19A, the loop through common dimensions1910 comprises assigning the “Leaf Members of Common Dimension Selection” to the “Alternate Common Dimension Selection” parameter, as indicated byreference1912. Afterstep1912, a check is made to determine if there are any more Common Dimension members to consider as indicated by reference1914. If yes, then the next Common Dimension member is considered and the looping operation in step1910 is repeated.
• If there are no more common dimension members to consider (as determined in step1914), then the loop through Source Dimension members is performed, as indicated by reference1920. During the looping operation, the process1900 checks if the source dimension is equal to accounts, as indicated byreference1922. If yes, the process1900 is configured to set the parameter “AlternateFrom Accounts Selection” to the “Accounts Selection”, and the parameter “AlternateTo Accounts Selection” is set as the “Contra Account”, as indicated byreference1924. Afterstep1924, a check is made to determine if there are any more Source Dimension members to consider as indicated byreference1926. If yes, then the next Source Dimension member is considered instep1928 and the looping operation in step1920 is repeated. If the source dimension is not set to Accounts (as determined in decision block1922), then the process1900 is configured to set the parameter “Alternate Source Dimension Selection” to the “Leaf Members of Source Dimension Selection”, as indicated byreference1923. A check then is made instep1926 to determine if there are any more Source Dimension members to consider. If yes, then the next Source Dimension member is considered instep1928 and the looping operation in step1920 is repeated.
• Referring toFIGS. 19A and 19B, if the last source dimension has been considered (as determined in step1926), then the process1900 is configured to execute a looping operation through the Alternate Common Dimension Combinations, as indicated byreference1930. As shown, the looping operation includes an internal loop for looping through Alternate Dimension Combinations as indicated by reference1940. For looping through the Source Dimension Combinations, the process1900 reads the “Cube Value” associated with the Alternate Dimension Combinations (the loops instep1930 and1940) and the AlternateFrom Accounts Selection, as indicated byreference1942. Next in step1944, the process1900 assigns the “Cube Value” to the parameter “Cube Value” multiplied by −1, and the Cube Value parameter is written to the cube for the Alternate Dimension Combination/Alternate To Accounts Selection, as indicated by reference1946. After step1946, a check is made to determine if there are any more Source Dimension Combinations to consider as indicated byreference1948. If yes, then the next Source Dimension Combination is considered instep1949 and the looping operation in step1940 is repeated. If all the last source dimension combinations have been considered (as determined in step1948), then a check is made in step1950 to determine if there are more common dimension combinations to consider. If yes, then the next common dimension combination is considered as indicated by reference1952 and the looping operation is repeated in1930, as described above. If the last common dimension combination has been considered (as determined in step1950), then the process for generating a contra account entry1900 terminates or ends as indicated by reference1960, and control returns to the calling process or function, for example, thepost processing function1800 inFIG. 18.
• In operation, the generate contra account entry option allows data to be copied back into selected Source dimension members for a single Account member. Because data cannot be stored into non-leaf members, the selected members for both Common and non-Account Source dimension members are adjusted to include leaf members below the selected Source dimension members. Data in these members is then copied from the source account to the contra account.
• The functionality and features associated with the server120 (FIG. 1) and/or the client machines110 (FIG. 1) and/or the user interface screens or windows (FIGS. 2 to 6) as described above and in accordance with the embodiments may be implemented in the form of one or more software objects, components, or computer programs or program modules in the server and/or the client machines. Further, at least some or all of the software objects, components or modules can be hard-coded into processing units and/or read only memories or other non-volatile storage media in the mobile communication device, server and/or other components or modules depicted in the drawings. The specific implementation details of the software objects and/or program modules will be within the knowledge and understanding of one skilled in the art.
• The present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. Certain adaptations and modifications of the invention will be obvious to those skilled in the art. Therefore, the presently discussed embodiments are considered to be illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (26)

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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 6, wherein said source-target dimensions comprise time-based target dimensions and non-time based target dimensions.

8. The system as claimed inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 14, wherein said data spread operation is configured for a data value specified by a user.

16. The system as claimed inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 22, wherein said source-target dimensions comprise time-based target dimensions and non-time based target dimensions.

25. The method as claimed inclaim 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.

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