Question

In your own word, explain why do designers use Denormalization? What is the limitation of using Denormalization? Name and explain a better alternative approach than Denormalization.

Note:

Please I need a short answer only on paragraph and simple words.

Answer 1

Denormalization is an approach to speeding up read-oriented data retrieval performance in a relational database, where the database administrator selectively adds back specific instances of redundant data after the data structure has been normalized.

Using normalization in SQL, a database will store different but related types of data in separate logical tables, called relations. When a query combines data from multiple tables into a single result table, it is called a join. The performance of such a join in the face of complex queries is often the occasion for the administrator to explore the denormalization alternative.

The limitations:

• Denormalization usually speeds retrieval but can slow updates.
• Denormalization is always application specific and therefore requires to be evaluated if the application changes.
• Denormalization can increase the size of tables.
• Denormalization can make update and insert code difficult to write.
• Data redundancy necessitates more storage.
• Denormalization does not maintain any data integrity.
• Waste storage space.

Here's a better alternative, when you decide not to fully normalize: adopt some design discipline that yields certain benefits, even when that design discipline departs from full normalization. As an example, there is star schema design, widely used in data warehousing and data marts. This is a far more coherent and disciplined approach than merely denormalizing by whimsy. There are specific benefits you'll get out of a star schema design, and you can contrast them with the update anomalies you will suffer because star schema design contradicts normalized design.

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