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  2. BigQuery - Wikipedia

    en.wikipedia.org/wiki/BigQuery

    BigQuery is a managed, serverless data warehouse product by Google, offering scalable analysis over large quantities of data. It is a Platform as a Service ( PaaS ) that supports querying using a dialect of SQL .

  3. Template:Extract - Wikipedia

    en.wikipedia.org/wiki/Template:Extract

    This template can extract information from a date, or can format a date. Time units can be added to a date. Syntax ... show date as "month day, year" show=ymd:

  4. Dimension (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Dimension_(data_warehouse)

    A time dimension with a grain of seconds in a day will only have 86400 rows. A more or less detailed grain for date/time dimensions can be chosen depending on needs. As examples, date dimensions can be accurate to year, quarter, month or day and time dimensions can be accurate to hours, minutes or seconds.

  5. List of SQL reserved words - Wikipedia

    en.wikipedia.org/wiki/List_of_SQL_reserved_words

    Reserved words in SQL and related products In SQL:2023 [3] In IBM Db2 13 [4] In Mimer SQL 11.0 [5] In MySQL 8.0 [6] In Oracle Database 23c [7] In PostgreSQL 16 [1] In Microsoft SQL Server 2022 [2]

  6. Form 990 - Wikipedia

    en.wikipedia.org/wiki/Form_990

    An annual extract of tax-exempt organizational data, which covers selected financial data from filters of Form 990, 990-EZ, and 990-PF, with data available from calendar year 2012 to the most recent year for which filing and statistics compilation is complete. [21] This is also available as a public dataset on Google BigQuery. [22]

  7. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    These viewpoints are sometimes called dimensions (such as looking at the same sales by salesperson, or by date, or by customer, or by product, or by region, etc.). Databases configured for OLAP use a multidimensional data model, allowing for complex analytical and ad hoc queries with a rapid execution time. [7]

  8. Spanner (database) - Wikipedia

    en.wikipedia.org/wiki/Spanner_(database)

    Cloud Spanner Booth at Google Cloud Summit. Spanner is a distributed SQL database management and storage service developed by Google. [1] It provides features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.

  9. Snappy (compression) - Wikipedia

    en.wikipedia.org/wiki/Snappy_(compression)

    Snappy (previously known as Zippy) is a fast data compression and decompression library written in C++ by Google based on ideas from LZ77 and open-sourced in 2011. [3] [4] It does not aim for maximum compression, or compatibility with any other compression library; instead, it aims for very high speeds and reasonable compression.