Aggregating your data is a simple way to reduce the information down to a smaller list of summarized information. There are two core elements when you do this. First you want to decide how you want to look at the data. Instead of looking at every single contact in your data, you may decide that you only need to see the companies that they work for, or maybe the city and state that they live in. In this first part, the data will be reduced to a unique list of values. The second decision to make is how you want the summarize the rest of the information. You may want to see how many people work in each corporation, or possibly the average age of all the people in each unique combination of city and state.
There are multiple ways to summarize in Excel. Choosing which method to use is your first decision. There is a "Consolidate" and a "Subtotal" button on the Data menu. They are good for very simple aggregations but are very limited. More often this kind of activity would be done using a Pivot Table. While the Pivot Table is a bit more involved to understand, it is much more flexible and has multiple applications. The dynamic capabilities with a Pivot Table can also make it difficult to use the results in other areas of a spreadsheet.
To aggregate within Paxata, select the Shape tool.
The default shaping method it will choose is "Group By" so you don't have to change anything here.
Select the columns that you want to create a unique list of values. You can pick columns from a list or type in the column names.
Next, select how you want to aggregate your information and which column to apply it to. There are many options to choose from.
Using the + and - on the right side, you can add or remove aggregates. Note in the example below that you can aggregate the same column multiple ways. In the case of "City", the aggregate will generate a list of unique cities with the "Count Distinct", and it will show the list of the cities in the "Array".
The names of the columns can be changed from their default.
For additional information, please refer to Group By Aggregate Functions