Power Embedded Pricing Calculator

Power Embedded Pricing Calculator

Notes on Power BI Embedded/Fabric capacity pricing:

  • The minimum number of users on the platform is 20. If you use less than 20 users, you will pay the amount equivalent to 20 users.
  • The lowest capacity Fabric (F2) is cheaper than the lowest capacity Embedded (A1) but has 4x fewer vCores.
  • The values presented in the table above may change due to capacity price changes by Microsoft or variations in the dollar exchange rate.
  • An assessment of the environment is necessary to define the most suitable capacity according to the volume of data, sizes of the data sets and other factors that influence performance, such as RLS, quantity and duration of updates, incremental updates, etc.

What capacity do I need for my company?

To estimate how many users Power Embedded is cheaper than your current license, we depend on some information about your environment and what type of licensing you currently use.

Our commercial team will survey information in your environment to previously assess how our solution can achieve the maximum possible savings, without losing performance, in a personalized and individual analysis for each client.

For Power BI Pro licenses, and in companies where the report does not need to be available 24 hours a day, from 20 users onwards you can save 50% compared to the cost of Pro licenses. If you use a Premium Per User (PPU) license , the economy reaches 76%.

If your environment has several large reports (over 200 MB), the Fabric capacity may not be suitable and you may need to use the Embedded capacity.

In this scenario, from 30 users onwards you will already be saving when using Power Embedded, and the greater the number of users, the greater the savings in relation to your current license.

The table below can help visualize scenarios when Power Embedded is more advantageous:


And this table below demonstrates the existing capabilities of Power BI Embedded

Our BI Consulting technical team (contracted separately) will be available to be used to optimize models or redesign the client's architecture to use Analysis Services as a data processing layer and be able to process large volumes of data.