Model-driven apps are less customizable, require even less code than Canvas apps and are more component-focused. As the name suggests, app makers essentially have a "model" of what the app will look like and feel like and will only have control over the various views and components added to the application. The layout and overall "feel" of the app is essentially already built for you.

While with Canvas applications there are many data sources to choose from, Model-driven applications are only connected to Dataverse data. As you already know, these applications are less customizable than Canvas applications. They are focused on modeling business data, defining business processes, and composing the application. Let's take a look into each of these a little deeper.

Modeling business data means designing the architecture of the data structure the app will be looking at. Meaning, what data will be used and how does that data relate to other data? Defining business processes is a key feature of Model-driven apps. These business processes can be very simple or extremely complex. But, however complicated the process, the main idea is that the user is guided through, step by step, so the process can be more automated, consistent, and standardized.

Composing the application. The composition of the application could be broken down into three sections: UI, Logic, and Visualizations. Let's first look at UI. UI includes the Site Map, Forms and Views that we can add to the application. Logic means the business process flows that we can set up, workflows, other actions and business rules. Visualizations include charts, dashboards and Power BI, which Power BI tiles can be embedded into the application.

For advanced Model-driven application making, the "Solution Explorer" allows you to manage all of the app components in a hierarchy or tree view. And that's it for this lecture. In the next lecture we'll talk about exploring the possibilities and use cases for Model-driven applications.