Drag and Drop Transformations

Drag-and-drop Transformations feature is currently in BETA phase.

Hevo provides the following drag-and-drop transformation blocks by default. You can configure them for your use and test them before deploying:

Control Functions

• If Else

Date Functions

• Change Datetime Field Value

• Format Date to String

• Parse Date From String

Event Manipulation

• Add Field

• Change Field Value

• Drop Events

• Drop Fields

• Find & Replace

• Rename Events

• Rename Fields

JSON Manipulation

• Flatten JSON

• Parse JSON From String

Mathematical Functions

• Format Number to String

• Parse Number from String

• Round-off Decimal Fields

Security Functions

• Hash Fields

• Mask Fields

String Functions

• Modify Text Casing

• Split Field

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Building a Transformation

You can drag and drop a transformation block to the canvas and configure its settings in the right pane.

1. Data Filters

By default, the transformation is applied to all Events and all Fields. However, you can filter the fields to be finally updated on the basis of the following:

Event Filters

• Event Type: The transformation is applied on the selected Event Type. For example, Event type of name, deals.

• Event Field: The transformation is applied on all Events that have this Event Field or Event Field Value. You can filter Events based on the properties of the Event. For example, you can select all Events that contain a field called price. This means the field-level filters, if any, and the transformation, will be applied on all Events that have the field, price. This does not mean that the intent is to apply the transformation only on the field price.

  Note: Events not matching the filters in a transformation block remain unchanged.

Field Filters

• Field Name: The transformation is applied on the specified fields. For example, in the Event Type deals containing a field by the name price, if a field with the name archived is present, the transformation must be applied on it.

• Field Value: The transformation is applied on all fields that have this value. For example, if the value of the archived field is true, the transformation must be applied on it.

Then, the final condition is derived as: For Event of Type deals and having the field price, if the value of the archived field is true, then apply the transformation as specified in the Settings.

Note: In case the field on which the transformation is applied is of the type Array or List, the transformation is applied to each element of the list instead of the list itself. Exception to this are: “Create separate fields while splitting” and “Flatten JSON”, where the transformation cannot be applied to the list.

You can select the appropriate operator and values for each of these filters.

2. Transformation settings

Settings define the action to be taken. For example, Field Name and New Field Name define which field name has to be changed and what its new value should be. The Settings are listed below the filters.

3. Transformation workflows

You can apply multiple transformations to the data by creating a workflow using the required transformation blocks. If each transformation is independent of the others, the sequence in which you connect the blocks is immaterial, and each transformation can call a different Event Type. However, if each block builds upon the previous, then the sequence of connecting the blocks is important. A sequential workflow can be designed on one Event Type only.

The Events not matching the filters remain unchanged. In addition, all Events are passed on to the next transformation block.

Note: You can drag and drop a block into an existing workflow sequence.

4. Incorrect settings

In case settings are missing or incorrect, an indicator is displayed next to the block. Hover the mouse over it to view the error text.

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Features and Limitations

You can use only the blocks provided by Hevo to build the transformation. To design your own transformation, switch to the Python code option. Alternatively, contact Hevo Support.

• Currently, you cannot combine both Python-based and drag-and-drop blocks in the same transformation.

• While building a transformation filters must be added in the order in which these will be applied on the data.

• You must be in the Build tab to delete or add transformation blocks or specify the filters and settings.

• The IF-ELSE block branches your code to apply the conditional transformation. Currently, you cannot merge the branches post-transformation.

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• Articles in this section
  • Transformations and Properties
  • Examples of Drag and Drop Transformations