7 - Preprocessing Logic: Mapping Datasets

📖 Task Introduction

Let’s now apply similar transforms to your two mapping datasets. Both need column names normalized and values cast as strings and standardized.

🔨 Task Instructions

1. Add transform nodes for priority_mapping_raw and status_mapping_raw (i.e., one for each).

2. For each dataset transform:

   • Name your transforms (in the upper left corner of the application) Preprocess priority mapping and Preprocess status mapping respectively
   • Cast the value column as string
   • Convert mapped_value columns to title case

3. In addition, for status_mapping_raw, see if you can find and configure transforms that remove whitespace and convert values to title case without any underscores. If you get stuck, see the hint for a suggested implementation.

   Hint:

   

4. Add pipeline outputs for each, called priority_mapping_preprocessed and status_mapping_preprocessed respectively.

5. Save and Deploy your pipeline to build the outputs in your /preprocessed folder.