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Why do we need to denormalize?
Denormalization is a database optimization technique in which we add redundant data to one or more tables. This can help us avoid costly joins in a relational database. In a traditional normalized database, we store data in separate logical tables and attempt to minimize redundant data.
Which are valid reasons to denormalize a production database?
In order to improve performance is almost always the answer. In the relational database environment, denormalization can mean fewer objects, fewer joins, and faster access paths. These are all very valid reasons for considering it.
When might it be a good idea to denormalize data?
Only if you need your database to perform better at particular tasks (such as reporting) should you opt for denormalization. If you do denormalize, be careful and make sure to document all changes you make to the database.
What is the only reason to denormalize a physical data model?
The only reason to ever denormalize a relational database design is to enhance performance. So the basic rule of thumb is to never denormalize data unless a performance need arises or your knowledge of the way your DBMS operates overrides the benefits of a normalized implementation.
What is denormalization and how does it work?
Denormalization helps data warehouse administrators ensure more predictable read performance. Examples of denormalization go beyond relational and SQL. Applications based on NoSQL databases often employ this technique — particularly document-oriented NoSQL databases.
When do you need to DENORMALIZE a database?
In many cases, the need for denormalization has waned as computers and RDBMS software have become more powerful, but since data volumes have generally increased along with hardware and software performance, OLAP databases often still use denormalized schemas.
When do you need to normalize a denormalized table?
This would be a denormalized table for speeding up reading the data. An important consideration for normalizing data is if the data will be read heavy or write heavy. Because data is duplicated in a denormalized database, when data needs to be added or modified, several tables will need to be changed.
Why is data consistency important in a denormalized system?
Another important consideration in a denormalized system is data consistency. In a normalized database, each piece of data is stored in one place; therefore, the data will always be consistent and will never produce contradictory results.