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  2. Aggregate data - Wikipedia

    en.wikipedia.org/wiki/Aggregate_data

    Aggregate data is high-level data which is acquired by combining individual-level data. For instance, the output of an industry is an aggregate of the firms’ individual outputs within that industry. [1] Aggregate data are applied in statistics, data warehouses, and in economics. There is a distinction between aggregate data and individual data.

  3. Aggregate (data warehouse) - Wikipedia

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

    An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.

  4. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    In other cases the aggregate cannot be computed without analyzing the entire set at once, though in some cases approximations can be distributed; examples include DISTINCT COUNT (Count-distinct problem), MEDIAN, and MODE. Such functions are called decomposable aggregation functions [4] or decomposable aggregate functions.

  5. Data aggregation - Wikipedia

    en.wikipedia.org/wiki/Data_aggregation

    When Yelp, for example, goes to update their Yelp listings, they will pull data from these local data aggregators. Publishers take local business data from different sources and compare it to what they currently have in their database. They then update their database it with what information they deem accurate.

  6. Statistical database - Wikipedia

    en.wikipedia.org/wiki/Statistical_database

    A statistical database is a database used for statistical analysis purposes. It is an OLAP (online analytical processing), instead of OLTP (online transaction processing) system. Modern decision, and classical statistical databases are often closer to the relational model than the multidimensional model commonly used in OLAP systems today.

  7. pandas (software) - Wikipedia

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

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series .

  8. Database object - Wikipedia

    en.wikipedia.org/wiki/Database_object

    A database object is a structure for storing, managing and presenting application- or user-specific data in a database. Depending on the database management system (DBMS), many different types of database objects can exist. [1] [2] The following is a list of the most common types of database objects found in most relational databases (RDBMS):

  9. Window function (SQL) - Wikipedia

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

    As an example, here is a query which uses a window function to compare the salary of each employee with the average salary of their department (example from the PostgreSQL documentation): [3] SELECT depname , empno , salary , avg ( salary ) OVER ( PARTITION BY depname ) FROM empsalary ;