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  2. Dimensional fact model - Wikipedia

    en.wikipedia.org/wiki/Dimensional_fact_model

    Figure 2 shows this example by joining the arcs that define a product VAT with a circular arc. Figure 3: a fact schema for the book sales fact. A convergence takes place when two dimensional attributes within a hierarchy are connected by two or more alternative paths of many-to-one associations. Convergences are represented by letting two or ...

  3. Conditional entropy - Wikipedia

    en.wikipedia.org/wiki/Conditional_entropy

    Assume that the combined system determined by two random variables and has joint entropy (,), that is, we need (,) bits of information on average to describe its exact state. Now if we first learn the value of X {\displaystyle X} , we have gained H ( X ) {\displaystyle \mathrm {H} (X)} bits of information.

  4. Bivariate analysis - Wikipedia

    en.wikipedia.org/wiki/Bivariate_analysis

    Graphs that are appropriate for bivariate analysis depend on the type of variable. For two continuous variables, a scatterplot is a common graph. When one variable is categorical and the other continuous, a box plot is common and when both are categorical a mosaic plot is common. These graphs are part of descriptive statistics.

  5. OLAP cube - Wikipedia

    en.wikipedia.org/wiki/OLAP_cube

    Given a relation of order N, consider a projection that subtends X, Y, and Z as the key and W as the residual attribute. Characterizing this as a function, f : (X,Y,Z) → W, the attributes X, Y, and Z correspond to the axes of the cube, while the W value corresponds to the data element that populates each cell of the cube.

  6. Dimension (data warehouse) - Wikipedia

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

    Type 5 (Combined Approach 1 + 4): Combination of type 1 and type 4. History is created through a second history table. Type 6 (Combined Approach 1 + 2 + 3): Combination of type 1, type 2 and type 3. History is created through separate row and attributes. Type 7 (Hybrid Approach): Both surrogate and natural key are used. [4]

  7. Multivariate interpolation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_interpolation

    In numerical analysis, multivariate interpolation or multidimensional interpolation is interpolation on multivariate functions, having more than one variable or defined over a multi-dimensional domain. [1] A common special case is bivariate interpolation or two-dimensional interpolation, based on two variables or two dimensions.

  8. Bivariate data - Wikipedia

    en.wikipedia.org/wiki/Bivariate_data

    For two qualitative variables (nominal or ordinal in level of measurement), a contingency table can be used to view the data, and a measure of association or a test of independence could be used. [3] If the variables are quantitative, the pairs of values of these two variables are often represented as individual points in a plane using a ...

  9. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...