Mapping Priority Levels and Transforming Data Using Bold Data Hub

In this article, we will demonstrate how to import tables from a CSV file, map priority levels 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

Mapping Priority Levels

Overview

Standardizing ticket priority levels into numeric values ensures consistency and simplifies processing. Common mappings include:

• Low → 1
• Medium → 2
• High → 3

Approach

We use a CASE statement to assign numeric values to the priority levels.

SQL Query for Mapping Priority Levels

SELECT 
    t.*, 
    CASE 
        WHEN t.priority = 'Low' THEN 1 
        WHEN t.priority = 'Medium' THEN 2 
        WHEN t.priority = 'High' THEN 3 
        ELSE NULL 
    END AS Mapped_Priority 
FROM {pipeline_name}.sample_csc_data t;