Grow's Data Transform Pipeline lets you add these transforms in any order. You can read this article to learn more about it.
Here is a brief overview of what each button does, going from top to bottom in the transform list. Each one has its own help article with more information and examples of how to use it.
Filter
Here you can select a specific column, and filter the information based on the data. Incredibly helpful to show data containing a specific keyword, or remove data that is not within a certain range.
Learn more about how to filter your data.
Group
This button lets you immediately aggregate grouped data from certain cells within your report. This is great for grouping data by week or month.
Learn more about how to group your data.
Aggregates
You can perform these actions (sum, count, average, cumulative sum, min, or max) based on a column of your choosing.
Learn more about how to use the Aggregates transform.
Calculated Columns
Calculated columns allows you to do math between two or more fields, change the format of a date, or extract a substring to display valuable information on your table charts.
Learn more about how to use calculated columns.
Sort & Limit
You can sort all of the data from the report based on a specific column. Ascending and Descending by number or alphabet.
Learn more about sorting and limiting your data.
SQL
Should any of the other transforms not meet your needs, SQL can be a powerful tool when you need something specific from your data. Use this transform to write your own SQL to manipulate your data.
Learn more about using the SQL transform.
Column Cleanup
This allows you to select which columns you want displayed. This can be particularly helpful when you have dozens of columns and want to focus on two or three at a time.
Learn more about selecting columns.
Pivot Table
Pivot tables take your data and combine different factors on your data and display it in a new table. It can sort, count, unique count, average, or find the min or max of your data. This gives you a lot of flexibility and analytical power to extract the significance from detailed data sets.
Learn more about how to use pivot tables.
Rename Column
If you'd like to customize the column names in your data to something of your choosing, you can use the Rename transform. This allows you to select an existing column, and then specify a new name.
Learn more about how to rename your columns.
Compare Dates
The Compare Dates transform allows you to compare your data across two different periods of time. This also ensures that your date ranges can update dynamically, meaning your metrics will stay updated instead of having to hard code in custom date ranges.
Learn more about how to use the Compare Dates transform.
Tag
The Tag transform allows you to create custom groupings categories which you can then apply to your data. It will create a new column with the tagged names you've created based on the criteria you select.
Learn more about the Tag transform.
Time Shifting
The Time Shifting transform lets you shift the timezone of your data. In Grow, data often comes in as UTC time, but that doesn't work for a lot of our customers. So we've added this transform so you don't have to write SQL to shift your data.
Learn more about Time Shifting.
Format Dates
Sometimes the data comes in formatted in a way that Grow won't recognize, which can then make it hard to use with other date-based transforms or chart formatting options. With this transform, you can help Grow recognize the parts of the incoming date format so it can reformat it into a standard YYYY-MM-DD format.
Learn more about the Format Dates transform.
If you do need to use Master SQL or SQL with the transform tools, more info can be found here.
Array Expander
The Array Expander Transform allows you to take a column of arrays and split each item in the array into its own row of data. This will effectively expand the rows of data you have to be at the granularity of each array item.
Learn more about the Array Expander transform.
JSON Explorer
The JSON Explorer Transform allows you to pull out data from a JSON data structure. JSON stands for JavaScript Object Notation and is a standard data format supported by many different databases and APIs.