## Working with cross tables

Pivot tables are matrix tables aimed to slice a measure with two or more dimensions.

Pivot tables are great for presenting aggregative data, but provide additional value for the data analysis as they use the *x* and *y* axes. This enables us to cross the data and compare two dimensions or more.

### Getting ready

In order to understand the pivot table capabilities, we will use a basic structure: two dimensions and one measure object.

### How to do it...

In the following pivot table, we will be able to analyze data by the **Year** or **Quarter** dimension. In the pivot body table, the revenue measure is presented as follows:

We can analyze each quarter row and view the increment/decrement in each year or analyze each year column and view the increment/decrement of the revenue along the quarter time progress.

Pivot tables are also great for showing what didn't happen. For example, let's analyze the following table:

Note that there is no revenue for the city **Berlin** in the year **2005**.

We will transform...