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What do you mean by denormalization?
Denormalization is the process of adding precomputed redundant data to an otherwise normalized relational database to improve read performance of the database. Normalizing a database involves removing redundancy so only a single copy exists of each piece of information.
Why would you like to Denormalize your design?
Denormalization is a strategy used on a previously-normalized database to increase performance. The idea behind it is to add redundant data where we think it will help us the most. We can use extra attributes in an existing table, add new tables, or even create instances of existing tables.
What are the reasons for Denormalizing the data in data warehouse?
This data warehousing strategy is used to enhance the functionality of a database infrastructure. Denormalization calls redundant data to a normalized data warehouse to minimize the running time of specific database queries that unite data from many tables into one.
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.
Is it necessary to DENORMALIZE data in a database?
Overall, denormalization should be justified and documented so future additions to the database or increased data sharing can address the denormalization issues. If necessary, the database might have to be renormalized and then denormalized with new information.
What is the role of denormalization in NoSQL?
Denormalization in data warehousing and NoSQL. In relational data warehouses, denormalization often plays an important role. This is particularly true in dimensional databases as prescribed by influential data warehouse architect and author Ralph Kimball.
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.