Denormalisation is suitable for read-heavy applications where query speed is a higher priority than data update efficiency.Īlso read: Top Data analytics bootcamp courses to pursue right now!

It is often done to improve query performance by reducing the need for complex joins. What is denormalisation, and when would you use it?Īns: Denormalisation is the process of intentionally introducing redundancy into a database by combining tables or introducing duplicate data. Normalisation helps maintain data consistency and minimises update anomalies. It involves breaking down data into smaller, related tables and eliminating data duplication. What is normalisation, and why is it important?Īns: Normalisation is the process of organising data in a database to reduce redundancy and improve data integrity. The physical data model translates the logical model into the technical specifications for a particular database system.

The logical data model focuses on the structure of the data independent of the specific database management system. Explain the difference between conceptual, logical, and physical data models.Īns: The conceptual data model represents high-level business concepts and relationships without concerning itself with technical details.

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