Hichert Partner Logo

Follow @ibcs_a

Table types

Table types are distinguished by their analytic purpose in time series tables, variance tables and cross tables, see figure SUCCESS rule EX 1.2. Tables serving more than one analytic purpose are called combined tables.

   

Time series tables

Time series tables are used for time series analyses, combining time columns with measure rows or structure rows.

A typical example for a time series table is a sales analysis by countries (rows) and years (columns).

   

Variance tables

Variance tables are used for scenario analyses, combining scenario columns and variance columns with measure rows or structure rows.

 

A typical example for a variance table is a sales analysis by countries (rows) showing different scenarios and different variances (columns).
 
   

Cross tables

Cross tables are used for structure analyses, combining structure columns with structure rows.

A typical example of a cross table is a sales table with countries in rows and products in columns.

 

   
 

Combined tables

Combined tables are used for multiple analyses. A combined table uses more than one column type and/or more than one row type presented either side by side or nested (see nested columns and nested rows).

 

The figures on the left show typical examples:

   

The first combined table shows a hierarchical structure of countries on three levels in the rows. The columns are nested: scenarios and variances are the same for both time periods November and January_November

   

The second combined table shows the measures of a calculation scheme in the rows. The columns are nested: The four quarters and the annual total are the same for both years.

   

The third combined table shows the same rows as the second one (measures of a calculation scheme). The nested columns now show PY and AC data as well as absolute and relative variances for two markets.

 
   
   
   
   
   
   
   
   
   
   
   

 

.
© 2017 IBCS Association. Licensed under Creative Commons BY-SA 4.0 International.