Normalizing and Denormalizing Values

You already know about the ADF Flatten activity from the Shredding JSON to Manage Data Elements section, which helps to denormalize data. There are two more such transformations to help normalize and denormalize datasets – Pivot and Unpivot.

Normalization and denormalization are two fundamental processes in data management. Normalization is like getting your data’s house in order. It ensures everything has its proper place, reducing clutter to enhance data integrity. It is all about breaking down a dataset into multiple tables and establishing clear relationships between them, thus making it simpler to find what you need without duplicates or confusion. It is like organizing a messy bookshelf into neat sections.

Conversely, denormalization is the process of combining multiple table data into a single table. This is done to improve the performance of the database by reducing the complexity of queries that join multiple tables...