The Logical Data-entry: Data Split & Splat

The logical data-entry, also called Data Split&Splat is a feature that allows you to enter numeric data at any aggregation level and automatically allocate it down to the underlying cells of the InfoCube. When a summary value (a total) is entered, the DS&S feature automatically allocates it down to the detail cells contributing to that summary based on underlying proportions, across any dimension of the InfoCube, such as products, customers, territories and time.

In a company where different people contribute to drawing up the budgets and forecasts, each individual can work along the lines closest to his/her own perception of the market and of the business. For example, the Sales Manager can make conjectures about the total sales by Customer Category while the Marketing Director might choose to view data by Product Category. Data consistency is granted at all times, without having to run batch processes, allocation procedures or consolidating the variations brought about by one or the other.

For example, suppose having a budget InfoCube structured by three dimensions: Month, Customer and Product. DS&S allows you to input values at any aggregation level for example on a summary view by quarter, State and Product. When a summary value is entered, it is instantly and proportionally allocated down to the elementary values contributing to that summary.

To enable logical data-entry,



The DS&S allocates summary values based on the underlying data proportions. It is not possible to enter a value on a summary cell if the summary value is zero. The data-entry InfoCubes are usually initialized through a procedure that feeds it with data using a defined criterion such as ”copy last year data” or ”apply the forecast function” or some other user defined method.


The logical data-entry allows you to enter data



The DS&S feature is available on all objects supporting data-entry. Please remember that cells having zero value are automatically disabled (data-entry is non possible).


See also the topic Data Block Functions for additional functions related to data-entry such as validation rules and suggested value.