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Defining dimensionality

Defining dimensionality - Power BI Tutorial

From the course: Power BI: Integrating AI

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Defining dimensionality

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- [Instructor] Dimensionality represents the high-level attributes within dataset fields. It's a key concept for working in Power BI and also in AI models. In data modeling, we refer to the attribute values in fields like category, location, or dates as dimensions. Low dimensionality refers to data with few dimension fields. This makes the data points within it more alike because they're more likely to share many of the same attribute values. High dimensionality refers to data with a high number of dimension fields. Well, this means they're likely more different because there are more attribute values to distinguish between them. This can also make it harder to model because of increased calculation complexity and visualizing them in a two-dimensional plane, which gives it the name the curse of dimensionality. Let's start with a table visual with the average temperatures. This gives us the average temperature across all the data that we have in the Weather table in our model. As we…

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