Actions on datasets - Cloud

Talend Cloud Data Preparation User Guide

author
Talend Documentation Team
EnrichVersion
Cloud
EnrichProdName
Talend Cloud
task
Data Quality and Preparation > Cleansing data
EnrichPlatform
Talend Data Preparation

When pointing your mouse over your datasets, several actions are available to manage or sort them.

Dataset based on a local file:

Dataset based on a database, Amazon S3, Salesforce or located on a HDFS cluster:

The table below describes the different actions that you can perform on your datasets.

Icon Action Description
Rename your dataset After typing the new name of your dataset, click the green tick icon to validate.
Share your dataset Use this button to make your datasets accessible to the other members of your organization. They will be able to open and add preparations on your datasets.
Apply an existing preparation on your dataset When you add a dataset with a schema that is identical to another dataset you already have, you can apply an existing preparation to it.
Overwrite your dataset with another file If the local file you used as a dataset has changed since you created the dataset, you can refresh this dataset with the latest data.
Edit your dataset This button opens a menu where you can modify the parameters that you entered to access a dataset located on a database or HDFS cluster. You can also change the name of the dataset.
Copy your dataset You can duplicate a dataset if you need more than one copy of the same dataset. You will find the new copy at the top of the Datasets list.
Delete your dataset A confirmation dialog opens before deleting the dataset.
Certify your dataset When doing collaborative work, user with their role set as Administrator can certify a dataset to indicate that this dataset has been validated. Clicking a first time on this icon will put the dataset in a "certification pending" state. Click one more time to certify the dataset.
Add a dataset to your favorites Adding a dataset to your favorites makes it easier for you to find when creating a new preparation based on your datasets.