# Step 2: Summarize the data
<a name="getting-started.02"></a>

In this step, you build a DataBrew recipe—a set of transformations that can be applied to this dataset and others like it. When the recipe is complete, you publish it so that it's available for use.

In the game of chess, players can be rated based on how well they perform against other players. (For more information, see [https://en.wikipedia.org/wiki/Chess_rating_system](https://en.wikipedia.org/wiki/Chess_rating_system)). For this tutorial, you focus on only the games where both players were Class A, meaning that their ratings were 1800 or more.

**To summarize the data**

1. On the transformation toolbar, choose **Filter**, **By Condition**, **Greater than or equal to**.

1. Set these options as follows:
   + **Source column** - `white_rating`
   + **Filter condition** – Greater than or equal to 1800

   To see how the transform works, choose **Preview changes**. Then choose **Apply**.

1. Repeat the previous step, but this time set **Source column** to `black_rating`. After you apply your changes, the sample data contains only those games where the players on each side (black and white) were Class A or above.

1. Summarize the data to determine how many games were won by each side. To do this, on the transformation toolbar, choose **Group**.

1. For the **Group** properties, do the following:

   1. In the first row, choose `winner` for **Column name**. Leave **Aggregate** set to **Group by**.

   1. In the second row, choose `victory_status` for the **Column name**. Leave **Aggregate** set to **Group by**.

   1. Choose **Add another column**. 

   1. In the third row, choose `winner` for **Column name**. Set **Aggregate** to **Count**.

   1. For **Group type**, choose **Group as new table**. The preview pane shows you what the result will look like.

   1. Choose **Finish**.

1. Choose **Publish** to save your work, at right on the recipe pane. 

1. For **Version Description**, enter **First version of my recipe**. Then choose **Publish**.