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  2. Data cleansing - Wikipedia

    en.wikipedia.org/wiki/Data_cleansing

    Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database.It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. [1]

  3. Delimiter-separated values - Wikipedia

    en.wikipedia.org/wiki/Delimiter-separated_values

    Most database and spreadsheet programs are able to read or save data in a delimited format. Due to their wide support, DSV files can be used in data exchange among many applications. A delimited text file is a text file used to store data, in which each line represents a single book, company, or other thing, and each line has fields separated ...

  4. Property list - Wikipedia

    en.wikipedia.org/wiki/Property_list

    The Python programming language has a builtin plistlib module to read and write plist files, in Apple's XML or in binary (since Python 3.4). [28] ProperTree is a cross-platform editor that makes use of this library. [29] A third-party library called ccl-bplist has the additional ability to handle NSKeyedArchiver UIDs. [19]

  5. Data dictionary - Wikipedia

    en.wikipedia.org/wiki/Data_dictionary

    The terms data dictionary and data repository indicate a more general software utility than a catalogue. A catalogue is closely coupled with the DBMS software. It provides the information stored in it to the user and the DBA, but it is mainly accessed by the various software modules of the DBMS itself, such as DDL and DML compilers, the query optimiser, the transaction processor, report ...

  6. Wide-column store - Wikipedia

    en.wikipedia.org/wiki/Wide-column_store

    A wide-column store (or extensible record store) is a type of NoSQL database. [1] It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table. A wide-column store can be interpreted as a two-dimensional key–value store. [1]

  7. Referential integrity - Wikipedia

    en.wikipedia.org/wiki/Referential_integrity

    A table (called the referencing table) can refer to a column (or a group of columns) in another table (the referenced table) by using a foreign key. The referenced column(s) in the referenced table must be under a unique constraint, such as a primary key. Also, self-references are possible (not fully implemented in MS SQL Server though [5]).

  8. Column (data store) - Wikipedia

    en.wikipedia.org/wiki/Column_(data_store)

    A column consists of a (unique) name, a value, and a timestamp. A column of a distributed data store is a NoSQL object of the lowest level in a keyspace. It is a tuple (a key–value pair) consisting of three elements: Unique name: Used to reference the column; Value: The content of the column.

  9. Table (information) - Wikipedia

    en.wikipedia.org/wiki/Table_(information)

    This is an injective relation: each combination of the values of the headers row (row 0, for lack of a better term) and the headers column (column 0 for lack of a better term) is related to a unique cell in the table: Column 1 and row 1 will only correspond to cell (1,1); Column 1 and row 2 will only correspond to cell (2,1) etc.