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  2. Block contention - Wikipedia

    en.wikipedia.org/wiki/Block_contention

    In database management systems, block contention (or data contention) refers to multiple processes or instances competing for access to the same index or data block at the same time. In general this can be caused by very frequent index or table scans, or frequent updates.

  3. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").

  4. Data corruption - Wikipedia

    en.wikipedia.org/wiki/Data_corruption

    Data corruption refers to errors in computer data that occur during writing, reading, storage, transmission, or processing, which introduce unintended changes to the original data. Computer, transmission, and storage systems use a number of measures to provide end-to-end data integrity , or lack of errors.

  5. Data scrubbing - Wikipedia

    en.wikipedia.org/wiki/Data_scrubbing

    As a copy-on-write (CoW) file system for Linux, Btrfs provides fault isolation, corruption detection and correction, and file-system scrubbing. If the file system detects a checksum mismatch while reading a block, it first tries to obtain (or create) a good copy of this block from another device – if its internal mirroring or RAID techniques are in use.

  6. Data degradation - Wikipedia

    en.wikipedia.org/wiki/Data_degradation

    Data degradation is the gradual corruption of computer data due to an accumulation of non-critical failures in a data storage device. It is also referred to as data decay, data rot or bit rot. [1] This results in a decline in data quality over time, even when the data is not being utilized.

  7. Data Integrity Field - Wikipedia

    en.wikipedia.org/wiki/Data_Integrity_Field

    Data Integrity Field (DIF) is an approach to protect data integrity in computer data storage from data corruption. It was proposed in 2003 by the T10 subcommittee of the International Committee for Information Technology Standards. [1] A similar approach for data integrity was added in 2016 to the NVMe 1.2.1 specification. [2]

  8. Block (data storage) - Wikipedia

    en.wikipedia.org/wiki/Block_(data_storage)

    In computing (specifically data transmission and data storage), a block, [1] sometimes called a physical record, is a sequence of bytes or bits, usually containing some whole number of records, having a maximum length; a block size. [2] Data thus structured are said to be blocked. The process of putting data into blocks is called blocking ...

  9. Data integrity - Wikipedia

    en.wikipedia.org/wiki/Data_integrity

    An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...