Compliance Validation and Transforming Data Using Bold Data Hub

In this article, we will demonstrate how to import tables from a CSV file, validate contacts regions through transformations, and move the cleaned data into the destination database using Bold Data Hub. Follow the step-by-step process below.

Sample Data Source:

Sample CSC Data

Creating Pipeline

Learn about Pipeline Creation

Applying Transformation

• Go to the Transform tab and click Add Table.

• Enter the table name to create a transform table for customer satisfaction summary.

Note: The data will initially be transferred to the DuckDB database within the designated {pipeline_name} schema before undergoing transformation for integration into the target databases. As an illustration, in the case of a pipeline named “customer_service_data”, the data will be relocated to the customer_service_data table schema.

Learn more about transformation here

Contacts Validation

Overview

To ensure data adheres to internal policies, ticket records should contain valid contact details such as phone numbers. This validation helps maintain data integrity and improves communication accuracy.

Approach

We use a CASE statement with a regexp_matches function to check if phone numbers follow a 10-digit numeric format.

SQL Query for Contacts Validation

SELECT 
    Ticket_ID, 
    Customer_ID, 
    Phone, 
    CASE 
        WHEN regexp_matches(CAST(Phone AS varchar), '^[0-9]{10}$') 
        THEN 'Valid' 
        ELSE 'Invalid Phone' 
    END AS Phone_Validation 
FROM {pipeline_name}.sample_csc_data;