Accessing the preparation from Talend Data Preparation - 7.1

Data Preparation

author
Talend Documentation Team
EnrichVersion
Cloud
7.1
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Data Integration
Talend Data Management Platform
Talend Data Services Platform
Talend ESB
Talend MDM Platform
Talend Real-Time Big Data Platform
task
Data Governance > Third-party systems > Data Preparation components
Data Quality and Preparation > Third-party systems > Data Preparation components
Design and Development > Third-party systems > Data Preparation components
EnrichPlatform
Talend Data Preparation
Talend Studio

Procedure

  1. In the design workspace, select tDataprepRun and click the Component tab to define its basic settings.
  2. In the URL field, type the URL of the Talend Data Preparation or Talend Cloud Data Preparation web application, between double quotes. Port 9999 is the default port for Talend Data Preparation.
  3. In the Username and Password fields, enter your Talend Data Preparation or Talend Cloud Data Preparation connection information, between double quotes.
    If you are working with Talend Cloud Data Preparation and if:
    • MFA ( Multi Factor Authentication) is enabled, enter an access token in the field.
    • MFA is not enabled but SSO (Single Sign-On) is configured, enter either an access token or your password in the field.

      It is recommend to use tokens as passwords will soon be obsolete and disappear.

    • MFA is not enabled and SSO is not configured, enter either an access token or your password in the field.
  4. Click Choose an existing preparation to display a list of the preparations available in Talend Data Preparation or Talend Cloud Data Preparation, and select datapreprun_scenario.

    This scenario assumes that a preparation with a compatible schema has been created beforehand.

  5. Click Fetch Schema to retrieve the schema of the preparation, datapreprun_preparation in this case.
    The output schema of the tDataprepRun component now reflects the changes made with each preparation step. The schema takes into account columns that were added or removed for example. By defaut, the output schema will use the String type for all the columns, in order not to overwrite any formatting operations performed on dates or numeric values during the preparation.