The use cases described in this document show several way of using Talend Cloud Data Preparation to perform formatting or cleansing operations to your data.
- The Customers dataset is used as source for the Standardize preparation. It shows how you can standardize state names, delete invalid records, consolidate phone numbers, change their format as well as date formats, or use a masking function to protect data. Finally, the Magic Fill function is used to convert dates to the corresponding day of the week.
- The Build_email preparation uses the Marketing Leads and the Emails Reference datasets and joins them in order to recreate emails addresses from customers names, company names, and their corresponding domain addresses.
In addition to these preparations that are available directly within the application, you can download additional datasets from the Downloads tab in the left panel of this page and use them to complete the following examples:
- Based on the CRM_export.xlsx dataset, build a preparation to consolidate in a new column all the mobile phones or landline phone numbers of your customers to make sure you have at least a working number for each.
- The marketing_leads.csv and emails_reference.csv datasets can be used together in the same preparation via a lookup operation to join the information about companies domain addresses and recreate entire email addresses.
- With the HRMS_export.xlsx dataset, learn how to change date formats and extract specific strings of characters from any column.
- The customer_contact_data.csv dataset can be improved by cleaning the empty and invalid datasets, and removing unnecessary blank spaces in text records.
- With the video_customers.xlsx dataset, follow a scenario to combine filters and create "if" conditions to isolate the data on a specific customers group.
- The car_dealership.xlsx dataset is used as base for a preparation illustrating how to use regular expression to match data that cannot be selected with usual filters.