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  2. Data build tool - Wikipedia

    en.wikipedia.org/wiki/Data_build_tool

    Dbt enables analytics engineers to transform data in their warehouses by writing select statements, and turns these select statements into tables and views. Dbt does the transformation (T) in extract, load, transform (ELT) processes – it does not extract or load data, but is designed to be performant at transforming data already inside of a ...

  3. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.

  4. Trino (SQL query engine) - Wikipedia

    en.wikipedia.org/wiki/Trino_(SQL_query_engine)

    Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...

  5. Template:Extract - Wikipedia

    en.wikipedia.org/wiki/Template:Extract

    1 if the date is in a leap year; 0 otherwise show=monthabbr: abbreviated name of month show=monthdays: number of days in the month of the date show=monthname: full name of month show=dmy: show date as "day month year" (default) show=mdy: show date as "month day, year" show=ymd: show date as "year-month-day"

  6. 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 ]

  7. Beautiful Soup (HTML parser) - Wikipedia

    en.wikipedia.org/wiki/Beautiful_Soup_(HTML_parser)

    Beautiful Soup is a Python package for parsing HTML and XML documents, including those with malformed markup. It creates a parse tree for documents that can be used to extract data from HTML, [3] which is useful for web scraping. [2] [4]

  8. Date windowing - Wikipedia

    en.wikipedia.org/wiki/Date_windowing

    Date windowing is a method by which dates with two-digit years are converted to and from dates with four-digit years. [1] The year at which the century changes is called the pivot year of the date window. [2] Date windowing was one of several techniques used to resolve the year 2000 problem in legacy computer systems. [3]

  9. SPARQL - Wikipedia

    en.wikipedia.org/wiki/SPARQL

    SPARQL (pronounced "sparkle", a recursive acronym [2] for SPARQL Protocol and RDF Query Language) is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.