Expense might appear in a simple spreadsheet product. In an OLAP system, such a calculation rule would normally calculate Profit for all combinations of the other dimensions in the cube (e.g., for all Products, for all Regions, for all Time Periods, etc.) using the respective Revenue and Expense data from those same dimensions. Part of the power of an OLAP system is the extensive multi-dimensional application of such a simply stated rule, which could be specified by the OLAP application builder or created by the end user in an interactive session. The true analytical power of an OLAP server, however, is evidenced in its ability to evaluate formulae where there are members from more than one dimension. An example is a multi-dimensional allocation rule used in business unit profitability applications. If, for example, a company has a Business Unit dimension and one of the business units (XYZ) is funding a special advertising campaign for Product A, and the other business units which also sell Product A are willing to share the advertising costs in proportion to their sales of the product, then the formula would be:
ADVERTISING EXPENSE = (PRODUCT A SALES/TOTAL CORPORATION PRODUCT A SALES) * ADVERTISING EXPENSE FOR PRODUCT A FOR BUSINESS UNIT XYZ Here, Advertising is from the Measures dimension wherever it intersects with other dimensions (e.g., Business Unit, Product), but Product A Sales is more specific; it is Sales from the Measures dimension restricted to the Product A member from the Product dimension. The Advertising Expense to be shared is the Advertising Expense for Product A spent by Business Unit XYZ that the business units which have non-zero sales of Product A agreed to share. These references to several dimensions within the same rule make it a Cross-Dimensional Formula.
GENERATION, HIERARCHICAL
Two members of a hierarchy have the same generation if they have the same number of ancestors leading to the top. For example, the top member of a dimension is from Generation 1. There may be two or more members in Generation 1 if there are multiple hierarchies in the dimension. NOTE: The terms generation and level are both necessary to describe sub-groups of dimension members, since, for example, although two siblings share the same parent and are therefore of the same generation, they won't be from the same level if one of the siblings has a child and the other doesn't. Synonyms: Peer, Sibling See: Level, Hierarchical Relationships, Parent, Children HIERARCHICAL RELATIONSHIPS
Any dimension's members may be organized based on parent-child relationships, typically where a parent member represents the consolidation of the members which are its children. The result is a hierarchy, and the parent/child relationships are hierarchical relationships. HORIZONTAL DIMENSION
See: Page Display HYPERCUBE
See: Cube, Array, Multi-dimensional INPUT MEMBERS
Input members have values that are loaded directly from either manual entry or by accessing another computer-based data source, as opposed to being calculated from the raw data. LEVEL, HIERARCHICAL
Members of a dimension with hierarchies are at the same level if, within their hierarchy, they have the same maximum number of descendants in any single path below. For example, in an Accounts dimension which consists of general ledger accounts, all of the detail accounts are Level 0 members. The accounts one level higher are Level 1, their parents are Level 2, etc. It can happen that a parent has two or more children which are different levels, in which case the parent's level is defined as one higher than the level of the child with the highest level. See: Generation, Hierarchical MEMBER, DIMENSION
A dimension member is a discrete name or identifier used to identify a data item's position and description within a dimension. For example, January 1989 or 1Qtr93 are typical examples of members of a Time dimension. Wholesale, Retail, etc., are typical examples of members of a Distribution Channel dimension. Synonyms: Position, Item, Attribute MEMBER COMBINATION
A member combination is an exact description of a unique cell in a multi-dimensional array, consisting of a specific member selection in each dimension of the array. See: Cell MISSING DATA, MISSING VALUE
A special data item which indicates that the data in this cell does not exist. This may be because the member combination is not meaningful (e.g., snowmobiles may not be sold in Miami) or has never been entered. Missing data is similar to a null value or N/A, but is not the same as a zero value. MULTI-DIMENSIONAL DATA STRUCTURE
See: Array, Multi-dimensional MULTI-DIMENSIONAL QUERY LANGUAGE
A computer language that allows one to specify which data to retrieve out of a cube. The user process for this type of query is usually called slicing and dicing. The result of a multi-dimensional query is either a cell, a two-dimensional slice, or a multi-dimensional sub-cube. NAVIGATION
Navigation is a term used to describe the processes employed by users to explore a cube interactively by drilling, rotating and screening, usually using a graphical OLAP client connected to an OLAP server. NESTING (OF MULTI-DIMENSIONAL COLUMNS AND ROWS)
Nesting is a display technique used to show the results of a multi-dimensional query that returns a sub-cube, i.e., more than a two-dimensional slice or page. The column/row labels will display the extra dimensionality of the output by nesting the labels describing the members of each dimension. For example, the display's columns may be:
January
February
March
Actual
Budget
Actual
Budget
Actual
Budget
Prod A
Prod B
Prod A
Prod B
Prod A
Prod B
Prod A
Prod B
Prod A
Prod B
Prod A
Prod B These columns contain three dimensions, nested in the user's preferred arrangement. Likewise, a report's rows may contain nested dimensions:
Chocolate Bars
Unit Sales
xxxx
xxxx
xxxx
Revenue
xxxx
xxxx
xxxx
Margin
xxxx
xxxx
xxxx
Fruit Bars
Unit Sales
xxxx
xxxx
xxxx
Revenue
xxxx
xxxx
xxxx
Margin
xxxx
xxxx
xxxx NON-MISSING DATA
Data which exists and has values, as opposed to null or missing data. OLAP CLIENT
End user applications that can request slices from OLAP servers and provide two- dimensional or multi-dimensional displays, user modifications, selections, ranking, calculations, etc., for visualization and navigation purposes. OLAP clients may be as simple as a spreadsheet program retrieving a slice for further work by a spreadsheet- literate user or as high-functioned as a financial modeling or sales analysis application. PAGE DIMENSION
A page dimension is generally used to describe a dimension which is not one of the two dimensions of the page being displayed, but for which a member has been selected to define the specific page requested for display. All page dimensions must have a specific member chosen in order to define the appropriate page for display. PAGE DISPLAY
The page display is the current orientation for viewing a multi-dimensional slice. The horizontal dimension(s) run across the display, defining the column dimension(s). The vertical dimension(s) run down the display, defining the contents of the row dimension(s). The page dimension-member selections define which page is currently displayed. A page is much like a spreadsheet, and may in fact have been delivered to a spreadsheet product where each cell can be further modified by the user. PARENT
The member that is one level up in a hierarchy from another member. The parent value is usually a consolidation of all of its children's values. See: Children PIVOT
See: Rotate PRE-CALCULATED/PRE-CONSOLIDATED DATA
Pre-calculated data is data in output member cells that are computed prior to, and in anticipation of, ad-hoc requests. Pre-calculation usually results in faster response to queries at the expense of storage. Data that is not pre-calculated must be calculated at query time. See: Derived Data/Members, Output Data REACH THROUGH
Reach through is a means of extending the data accessible to the end user beyond that which is stored in the OLAP server. A reach through is performed when the OLAP server recognizes that it needs additional data and automatically queries and retrieves the data from a data warehouse or OLTP system. ROLL-UP
See: Consolidate ROTATE
To change the dimensional orientation of a report or page display. For example, rotating may consist of swapping the rows and columns, or moving one of the row dimensions into the column dimension, or swapping an off-spreadsheet dimension with one of the dimensions in the page display (either to become one of the new rows or columns), etc. A specific example of the first case would be taking a report that has Time across (the columns) and Products down (the rows) and rotating it into a report that has Product across and Time down. An example of the second case would be to change a report which has Measures and Products down and Time across into a report with Measures down and Time over Products across. An example of the third case would be taking a report that has Time across and Product down and changing it into a report that has Time across and Geography down. Synonym: Pivot ROW DIMENSION
See: Page Display SCOPING
Restricting the view of database objects to a specified subset. Further operations, such as update or retrieve, will affect only the cells in the specified subset. For example, scoping allows users to retrieve or update only the sales data values for the first quarter in the east region, if that is the only data they wish to receive. SELECTION
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