The use case explains how to use the Profiling perspective of the studio to analyze customer email addresses and phone numbers. It uses out-of-box indicators and patterns on the columns and shows the matching and non-matching address data.
You can then use the Data Explorer perspective to browse the non-matching data.
The sequence of profiling customer data involves the following steps:
- Create a column analysis on customer email addresses and phone numbers.
- Connect to the database which holds the customer data from the analysis editor.
- Add indicators to provide simple statistics on data such as row , blank and duplicate counts.
- Add standard patterns against which to match email addresses and phone numbers.
- Execute the analysis to show results in tables and charts.
- Access a view of the analyzed data to see invalid records.