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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. Data redundancy - Wikipedia

    en.wikipedia.org/wiki/Data_redundancy

    The additional data can simply be a complete copy of the actual data (a type of repetition code), or only select pieces of data that allow detection of errors and reconstruction of lost or damaged data up to a certain level. For example, by including computed check bits, ECC memory is capable of detecting and correcting single-bit errors within ...

  4. 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).

  5. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.

  6. 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.

  7. Data reduction - Wikipedia

    en.wikipedia.org/wiki/Data_reduction

    Data reduction is the transformation of numerical or alphabetical digital information derived empirically or experimentally into a corrected, ordered, and simplified form. . The purpose of data reduction can be two-fold: reduce the number of data records by eliminating invalid data or produce summary data and statistics at different aggregation levels for various applications

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  9. 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.