Data Preparation (Docker)
Last updated
Last updated
Data Preparation component allows to run data preparation scripts on selected datasets. These datasets can be created from sources such as sandbox or by creating them using data connector. With Data Preparation, you can easily create data preparation with a single click. This automates common data cleaning and transformation tasks, such as filtering, aggregation, mapping, and joining.
All component configurations are classified broadly into 3 section
​​Basic Information​​
Meta Information
Select the Data Preparation from the Transformations group and drag it to the Pipeline Editor Workspace.
The user needs to connect the Data Preparation component with an In-Event and Out Event to create a Workflow as displayed below:
The following two options provided under the Data Center Type field:
Data Set
Data Sandbox
Navigate to the Meta Information tab.
Data Center Type: Select Data Set as the Data Center Type.
Data Set Name: Select a Data Set Name using the drop-down menu.
Preparation(s): The available Data Preparation will list under the Preparation(s) field for the selected Data Set. Select a Preparation by using the checkbox. Once the preparation is selected, it will display the list of transformation done in that selected preparation. Please see the below given image for reference.
Navigate to the Meta Information tab.
Data Center Type: Select Data Sandbox as the Data Center Type.
Data Sandbox Name: Select a Data Sandbox Name using the drop-down menu.
Preparation(s): The available Data Preparation will list under the Preparation(s) field for the selected Data Sandbox. Select a Preparation by using the checkbox. Once the preparation is selected, it will display the list of transformation done in that selected preparation. Please see the below given image for reference.
A success notification message appears when the component gets saved.
Save and Run the Pipeline workflow.
Click the Save Component in Storage icon.