Grow's Data Transform Pipeline lets you add these transforms in any order. You can read this article to learn more about it.
Grow has around 20 Transforms available for your use. There are three different sections of Transforms: Clean & Prepare, Analyze, and Advanced. Here is a brief overview of each transform, but if you want to learn more, each one has their own help article you can reference as well.
Clean & Prepare
Column Cleanup: The Column Cleanup Transform lets you select which columns you want displayed and change the order of them as well. This can be particularly helpful when you have dozens of columns and want to narrow down your data to a specific few.
Rename Column: The Rename Column Transform lets you customize the column names in your data to something of your choosing. This can clean up any column names and make them easier to read.
Tag: The Tag Transform lets you create custom grouping 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.
Data Type: The Data Type Transform lets you change the data type of a column to a different type. There are 4 data types used in Grow: Text, Numeric, Date, and Date Time.
Format as Date: The Format as Date transform helps in cases where a date column comes into Grow formatted in a way that isn’t recognized. This can make it hard to use 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.
If you do need to use Master SQL or SQL with the transform tools, more info can be found here.
Time Shifting: The Time Shifting transform lets you shift the timestamps of your date columns. Data often comes in as UTC time, but if you want to see it in your time zone, you can add or subtract the necessary hours to make view your data with the correct timestamp.
Date Difference: The Data Difference transform is used to calculate time between two different date columns or between a date column and a fixed or dynamic date. This Transform lets you get results back in different units including days, weeks, months, quarters, and years.
Concatenate: The Concatenate Transform lets you merge two or more columns of data (as well as free text), to create a new column of data. Common use cases include merging first name and last name to get full name or merging two id columns to get a unique id.
Find & Replace: The Find & Replace Transform lets you find specific strings (words, phrases, or characters) within a text field and replace them with another string. You may also remove a specific string from a text field, by finding a substring and replacing it with nothing.
Coalesce: The Coalesce Transform lets you find the first non-blank value between multiple columns and creates a new column with that non-blank value. This is useful if you have data for names in multiple columns and you want the full name if it’s available, but if it’s not available, you would like the first name or the last name.
Extract: You can extract only a part of information present in your column. This is helpful if you want to trim any portion, or if you want to split the data in multiple column.
Filter: The Filter Transform lets you select a specific column, and filter the information based on criteria you choose. This helps show data containing a specific keyword or remove data that is not within a certain range.
Group: The Group Transform lets you group and aggregate data from certain columns within your data. It is also useful in removing duplicate information.
Aggregates: The Aggregates Transform lets you perform these actions - sum, count, count unique, average, cumulative sum, min, max, or median - based on a column of your choosing.
Calculated Columns: The Calculated Columns Transform lets you do math between two or more columns, change the format of a date, or extract a substring to display valuable information in different ways.
Sort & Limit: The Sort & Limit Transform lets you sort all the data from the report based on a specific column. You can choose to sort ascending or descending by number or alphabet.
Pivot Table: The Pivot Table Transform takes the data from two columns and applies your chosen aggregate on a third column to display your data in a new table highlighting the relationship between these three columns. The aggregate options are sum, count, count unique, average, min, or max.
Compare Dates: The Compare Dates Transform lets you compare your data across two different periods of time. It creates columns for the base period and the comparison period so you can make sure the data is lined up correctly.
SQL: The SQL Transform can be a powerful tool when you need something specific from your data and the other transforms don’t meet that need. Use this transform to write your own SQL to manipulate your data.
Array Expander: The Array Expander Transform lets you 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.