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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. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    The base data and the dimension tables are stored as relational tables and new tables are created to hold the aggregated information. It depends on a specialized schema design. This methodology relies on manipulating the data stored in the relational database to give the appearance of traditional OLAP's slicing and dicing functionality.

  4. Aggregate project plan - Wikipedia

    en.wikipedia.org/wiki/Aggregate_project_plan

    An aggregate project plan (APP) is the process of creating development goals and objectives and using these goals and objectives to improve productivity as well as development capabilities. The purpose of this process is generally to ensure that each project will accomplish its development goals and objectives.

  5. Data aggregation - Wikipedia

    en.wikipedia.org/wiki/Data_aggregation

    The United States Geological Survey explains that, “when data are well documented, you know how and where to look for information and the results you return will be what you expect.” [2] The source information for data aggregation may originate from public records and criminal databases.

  6. 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.

  7. Forecasting - Wikipedia

    en.wikipedia.org/wiki/Forecasting

    Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis.

  8. HuffPost Data

    projects.huffingtonpost.com

    Interactive maps, databases and real ... Live election results and related data for Senate, House and governor's races ... 4/12 Presidential Forecast. Maps and charts ...

  9. OLAP cube - Wikipedia

    en.wikipedia.org/wiki/OLAP_cube

    An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.

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