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  2. Data blending - Wikipedia

    en.wikipedia.org/wiki/Data_blending

    In tableau software, data blending is a technique to combine data from multiple data sources in the data visualization. [17] A key differentiator is the granularity of the data join. When blending data into a single data set, this would use a SQL database join, which would usually join at the most granular level, using an ID field where ...

  3. Associative entity - Wikipedia

    en.wikipedia.org/wiki/Associative_entity

    Associative tables are colloquially known under many names, including association table, bridge table, cross-reference table, crosswalk, intermediary table, intersection table, join table, junction table, link table, linking table, many-to-many resolver, map table, mapping table, pairing table, pivot table (as used in Laravel—not to be ...

  4. Many-to-many (data model) - Wikipedia

    en.wikipedia.org/wiki/Many-to-many_(data_model)

    For example, think of A as Authors, and B as Books. An Author can write several Books, and a Book can be written by several Authors. In a relational database management system, such relationships are usually implemented by means of an associative table (also known as join table, junction table or cross-reference table), say, AB with two one-to-many relationships A → AB and B → AB.

  5. Join (SQL) - Wikipedia

    en.wikipedia.org/wiki/Join_(SQL)

    An inner join (or join) requires each row in the two joined tables to have matching column values, and is a commonly used join operation in applications but should not be assumed to be the best choice in all situations. Inner join creates a new result table by combining column values of two tables (A and B) based upon the join-predicate.

  6. Hash join - Wikipedia

    en.wikipedia.org/wiki/Hash_join

    The hash join is an example of a join algorithm and is used in the implementation of a relational database management system.All variants of hash join algorithms involve building hash tables from the tuples of one or both of the joined relations, and subsequently probing those tables so that only tuples with the same hash code need to be compared for equality in equijoins.

  7. Chase (algorithm) - Wikipedia

    en.wikipedia.org/wiki/Chase_(algorithm)

    To do so, the tableau can be chased by applying the FDs in F to equate symbols in the tableau. A final tableau with a row that is the same as t implies that any tuple t in the join of the projections is actually a tuple of R. To perform the chase test, first decompose all FDs in F so each FD has a single attribute on the right hand side of the ...

  8. Littlewood–Richardson rule - Wikipedia

    en.wikipedia.org/wiki/Littlewood–Richardson_rule

    A Littlewood–Richardson tableau. A Littlewood–Richardson tableau is a skew semistandard tableau with the additional property that the sequence obtained by concatenating its reversed rows is a lattice word (or lattice permutation), which means that in every initial part of the sequence any number occurs at least as often as the number +.

  9. Join dependency - Wikipedia

    en.wikipedia.org/wiki/Join_dependency

    In database theory, a join dependency is a constraint on the set of legal relations over a database scheme. A table T {\displaystyle T} is subject to a join dependency if T {\displaystyle T} can always be recreated by joining multiple tables each having a subset of the attributes of T {\displaystyle T} .