Qlik's approach to handling data science is through integration with third-party platforms using APIs. We can enable Qlik Sense (Desktop or Enterprise) to connect to Python, R, Spark, Java, C#, or other programming languages, leveraging the user's ability to analyze data. We can also use forecasting, clustering, correlations, or whatever we need to analyze data. As an example, we are going to use Python sklearn and R for data forecast modeling.

Using the related terms, Qlik enables AAI through SSE, extending the regular Qlik Indexing Engine (QIX) behavior by transferring data chunks from the Qlik Engine to other server(s) that implement a function that performs the calculation and returns the result to Qlik Engine. 

Before we take a closer look at the next section, you have to be familiar with the difference between the following screenshots. Here's the first one:

Here is the second one:

As you can see, there is another software component (which can be executed anywhere, from the same machine that Qlik Sense is running on, or even on another machine) that handles all calculations that could not be made by the Qlik Engine.