Types of Metrics

There are different kinds of metrics you can add to a model: additive metrics, non-additive metrics, and semi-additive metrics. This section explains the different kinds of metrics and how AtScale's aggregate system manages them.

You add a metric to a model by first identifying the fact dataset of your model, then applying aggregate calculations to the quantifiable dataset columns. The type of aggregate calculation you apply determines the type of metric it is.

• Additive Metrics

  Additive metrics are those whose values can be summarized for any dimension attribute of the model, and the results can be combined consistently.

• Non-Additive Metrics

  Non-additive metrics are those that cannot work with summarized values. They need to evaluate all dimension members individually to ensure accuracy.

• Semi-Additive Metrics

  Semi-additive metrics are those whose values can be summarized for some dimensions of a model, but not all. Ratios such as Average are also considered semi-additive metrics.

• Calculated Metrics

  A calculated metric uses an MDX expression, often in the form of a mathematical formula, to combine, evaluate, or manipulate other metrics defined in the model.