data-normalization

Vocabulary Word

Definition

'Data Normalization' is the process of reorganizing data in a database so that it meets certain conditions, reducing data redundancy and improving data integrity.

Examples in Different Contexts

In machine learning, 'data normalization' is a preprocessing step where numerical data fields are scaled to a standard range to ensure models train more effectively. A machine learning engineer might state, 'Data normalization is essential for algorithms to converge faster and reduce the computational complexity.'

Practice Scenarios

Software

Scenario:

I've noticed that the data across our SaaS application is not syncing in real-time. It could severely impact our user experience.

Response:

Normalizing the data could enable real-time sync and enhance the user experience across our SaaS application.

Business

Scenario:

Our customer database contains a lot of inconsistent and redundant information. This is affecting our marketing team's ability to segment accurately.

Response:

Should we employ data normalization techniques to clean up our customer database and improve segmentation?