Playbooks are workflows that can be automated. In these workflows, there are two situations where you would want to 'Transform Data'. The first one is when you need to trigger actions in response to a specific event or a data point. However, sometimes identifying the specific data point is not straightforward, you will have to transform the input data like a filter, convert formats, join, and so on. The second situation is when you want to send data out. Imagine you have a playbook set to do a lookup of the source IP addresses. You may want to take the results and send that information as an email. You can do most kinds of such simple and advanced data transformations in the playbook.
What you'll learn
How to transform or manipulate output data of steps?
How to transform data
Hover over the step whose output data you want to transform. Click + button.
Open Transform Data under Browse All in the step catalog. The following options are available.
Extract | Extract a single field or multiple fields into a new column from JSON. |
Filter | Filter rows from the input data using boolean expressions and filter columns directly by name. |
Add New Field | Add a new field/column to the input data. The new field's value can be expressed using Spark Functions. |
Parse | |
Join | Combine outputs of one or more steps in many different ways. |
Lookup | |
Combine Columns | Combine multiple individual columns to form one single JSON column using the steps available under Combine Columns |
Format | Convert between different formats of data like HTML to JSON, JSON list to Array, Table to HTML, JSON to Table and JSON to Markup Jira Text. |
Group by | Group the same values of a column together. Aggregate the rest of the column values for each grouped row using a function like Count, Average etc |
SQL Functions | Add a new field/column to the input data. The new field's value can be expressed using Spark Functions. |
Other |
Example of using 'Extract' to transform data
Extract JSON fields allow you to extract fields from a JSON column in the table.
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