Concept: Sheet Types

A standard sheet contains a simple grid of accounts and time periods. Common examples of standard sheets include expense sheets, revenue sheets, profit-and-loss sheets, balance sheets, and cash flow sheets.

Look for:

1 Accounts or levels down the rows. 

2 Levels or accounts in the drop-down menu. Swap the rows with the drop-down.  

3 Time across the columns. Change the time periods with Display Options.

4 Dimensions as columns with cells that have drop-down values. Not all standard sheets have dimensions. In order to select dimension, add a split. 

Standard sheets also have the Add Split , Delete Split , and Rename Split  buttons in the toolbar. See Add Splits and Rows.

Modeled sheets are for entering record-based data. The sheet has customized field names across the columns and records as rows. A modeled sheet contains the underlying business logic for modeling financial events, such as revenues generated from sales, monthly salaries of personnel, or the depreciation of capital purchases.

Look for:

1 Add Row   and Delete Row  buttons in addition to, or instead of, the add, delete, rename splits buttons. See Add Splits and Rows.

2 Labeled columns across the top and records listed down the rows. The column types determine how data is entered: either by typing in fields, or selecting from drop-downs. There are no row headers, only column headers.

Enter new information into existing rows or add new rows. Your admin may set a maximum number of rows a modeled sheet can display at once. If this is the case, you see a message stating how many rows you're seeing of the total. Use the filters, to uncover different sets of data.

A cube sheet is a type of sheet that allows for multi-dimensional data input in a few accounts across a potentially large set of dimensions.

Look for:

1 More display options in the toolbar: Pivot the sheet to view data in multiple ways. See Concept: Your Sheet View.

2 No level drop-down: Levels are a dimension to use as filters, columns, or rows. 

3 Alternative dimensions: Filter data, drag and drop into the columns and rows, and nest up to five dimensions in the rows.