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  2. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .

  3. Don't repeat yourself - Wikipedia

    en.wikipedia.org/wiki/Don't_repeat_yourself

    "Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.

  4. Data redundancy - Wikipedia

    en.wikipedia.org/wiki/Data_redundancy

    Data redundancy leads to data anomalies and corruption and generally should be avoided by design; [5] applying database normalization prevents redundancy and makes the best possible usage of storage. [ 6 ]

  5. Denormalization - Wikipedia

    en.wikipedia.org/wiki/Denormalization

    In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data. [1] [2] It is often motivated by performance or scalability in relational database software needing to carry out very large numbers of read ...

  6. Third normal form - Wikipedia

    en.wikipedia.org/wiki/Third_normal_form

    A database relation (e.g. a database table) is said to meet third normal form standards if all the attributes (e.g. database columns) are functionally dependent on solely a key, except the case of functional dependency whose right hand side is a prime attribute (an attribute which is strictly included into some key).

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points. This process condenses extensive ...

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  9. Data deduplication - Wikipedia

    en.wikipedia.org/wiki/Data_deduplication

    In computing, data deduplication is a technique for eliminating duplicate copies of repeating data. Successful implementation of the technique can improve storage utilization, which may in turn lower capital expenditure by reducing the overall amount of storage media required to meet storage capacity needs.