^{01.01.2005 00:00}

^{01.01.2005 01:00}

¹²

³⁷

^D1

^{01.01.2005 00:00}

^{01.01.2005 01:00}

¹⁴

³⁹

^D2

^{01.01.2005 01:00}

^{01.01.2005 02:00}

¹⁶

⁴¹

^D1

^{01.01.2005 01:00}

^{01.01.2005 02:00}

¹⁸

⁴⁵

^D2

^{01.01.2005 00:00}

^{01.01.2005 01:00}

¹²

¹⁴

³⁷

³⁹

^{01.01.2005 00:00}

^{01.01.2005 01:00}

¹⁶

¹⁸

⁴¹

⁴⁵

Identifier column for pivot columns

Any

Opt.

This column contains the respective queue name.

col1

Identifier columns for pivot rows

Any

Opt.

This is the Day Type column of the input table.

col2

Data columns

Any

Opt.

The data columns of the input table, e.g. number of calls, AHT, ...

col3

As you can see this is a table with a bunch of rows and way less columns.

If you want more columns and less rows a pivot table could help out.

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The following data node contains employee and customer counts as well as sales numbers by region (A, B) and time of day.

We want to pivot the table so that the number of employees by region is displayed for each time interval.

Choose the columns which are affected in the operation settings:

It is possible to select more than one data column and / or row identifier.

The resulting data node shows the number of employees in two columns, one for each region A and B.

The order of the columns in the resulting data node depend on the order in which the data are sorted in the original data node.
In this example, Identifier A shows up before B in the original data node, and therefore column order is C A, D B in the resulting data node.

-