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  2. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    Joining data from multiple sources (e.g., lookup, merge) and deduplicating the data; Aggregating (for example, rollup – summarizing multiple rows of data – total sales for each store, and for each region, etc.) Generating surrogate-key values; Transposing or pivoting (turning multiple columns into multiple rows or vice versa)

  3. Select (SQL) - Wikipedia

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

    Title Authors ----- ----- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1 Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:

  4. Staging (data) - Wikipedia

    en.wikipedia.org/wiki/Staging_(data)

    Staging area architectures range in complexity from a set of simple relational tables in a target database to self-contained database instances or file systems. [4] Though the source systems and target systems supported by ETL processes are often relational databases, the staging areas that sit between data sources and targets need not also be ...

  5. Data retrieval - Wikipedia

    en.wikipedia.org/wiki/Data_retrieval

    A query language, like for example Structured Query Language (SQL), is used to prepare the queries. SQL is an American National Standards Institute (ANSI) standardized query language developed specifically to write database queries. Each database management system may have its own language, but most are relational.

  6. View (SQL) - Wikipedia

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

    Views can represent a subset of the data contained in a table. Consequently, a view can limit the degree of exposure of the underlying tables to the outer world: a given user may have permission to query the view, while denied access to the rest of the base table. [2] Views can join and simplify multiple tables into a single virtual table. [2]

  7. 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 ...

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    mail.aol.com

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  9. Join dependency - Wikipedia

    en.wikipedia.org/wiki/Join_dependency

    A table is subject to a join dependency if can always be recreated by joining multiple tables each having a subset of the attributes of . If one of the tables in the join has all the attributes of the table T {\displaystyle T} , the join dependency is called trivial.