Matrices and Graph
Fun fact: this is only valid for domains that have a notion of "selfness", i.e. that there is such thing as an "identity matrix" for the quantities.<p>Consider the following square matrix:<p><pre><code>            TSLA APPL GOOG MSFT    
    Alice | 100   5     0    1
    Bob   |  0    30   100   5
    Carol |  2    2     2    2
    Dan   |  0    0     0  1000
</code></pre>
An input vector of stock prices gives an output vector of net worths. However, that is about the only way you can use this matrix. You cannot transform the table arbitrarily and still have it make sense, such as applying a rotation matrix -- it is nonsensical to speak of a rotation from Tesla-coordinates to Google-coordinates. The input and output vectors lacks tensor transformation symmmetries, so they are not tensors.<p>This is also why Principal Component Analysis and other data science notions in the same vein are pseudoscience (unless you evaluate the logarithm of the quantities, but nobody seems to recognize the significance of unit dimensions and multiplicative vs additive quantities)