Chapter 1: Introduction to Data Modeling in Power BI
Power BI is not just a reporting tool that someone uses to build sophisticated reports; it is a platform supplying a wide range of features from data preparation to data modeling and data visualization. It is also a very well-designed ecosystem, giving a variety of users the ability to contribute to their organization's data analysis journey in many ways, from sharing datasets, reports, and dashboards to using their mobile phones to add some comments to a report, ask questions, and circulate it back to relevant people. All of this is only possible if we take the correct steps in building our Power BI ecosystem. A very eye-catching and beautiful report is worth nothing if it shows incorrect business figures or if the report is too slow to render so the user does not really have the appetite to use it.
One of the most important aspects of building a good Power BI ecosystem is getting the data right. In real-world scenarios, you normally get data from various data sources. Getting data from the data sources and mashing it up is just the beginning. Then you need to come up with a well-designed data model that guarantees you always represent the right figures supporting the business logic so the report performs well.
In this chapter, we'll start by learning about the different Power BI layers and how data flows between the different layers to be able to fix any potential issues more efficiently. Then, we'll study one of the most important aspects of Power BI implementation, that is, data modeling. You'll learn more about data modeling limitations and availabilities under different Power BI licensing plans. Finally, we'll discuss the iterative data modeling approach and its different phases.
In this chapter, we'll cover the following main sections:
- Power BI Desktop layers
- What data modeling means in Power BI
- Power BI licensing considerations for data modeling
- The iterative data modeling approach
Understanding the Power BI layers
As stated before, Power BI is not just a reporting tool. As the focus of this book is data modeling, we would rather not explain a lot about the tool itself, but there are some concepts that should be pointed out. When we talk about data modeling in Power BI, we are indeed referring to Power BI Desktop as our development tool. You can think of Power BI Desktop like Visual Studio when developing an SQL Server Analysis Services (SSAS) Tabular model. Power BI Desktop is a free tool offering from Microsoft that can be downloaded from https://powerbi.microsoft.com/en-us/downloads/. So, in this book, we're referring to Power BI Desktop when we say Power BI unless stated otherwise.
The following illustration shows a very simple process we normally go through while building a report in Power BI Desktop:
Figure 1.1 – Building a new report process in Power BI
To go through the preceding processes, we use different conceptual layers of Power BI. You can see those layers in Power BI Desktop as follows:
Figure 1.2 – Power BI layers
Download the Microsoft Contoso Sales sample for Power BI Desktop from https://www.microsoft.com/en-us/download/confirmation.aspx?id=46801.
Let's discuss each point in detail:
- The Power Query (data preparation) layer
- The data model layer
- The data visualization layer
The data preparation layer (Power Query)
In this layer, you get data from various data sources, transform and cleanse that data, and make it available for other layers. This is the very first layer that touches your data, so it is a very important part of your data journey in Power BI. In the Power Query layer, you decide which queries load data into your data model and which ones will take care of data transformation and data cleansing without loading the data into the data model:
Figure 1.3 – Power Query
The data model layer
This layer has two views, the Data view and the Model view. In the Data view, you can see the data, and in the Model view, you can see the data models.
The Data view
After we are done with our data preparation in the Power Query layer, we load the data into the data model layer. Using the Data view, we can see the underlying data in our data model layer after it has been transformed in the data preparation layer. Depending on the connection mode, this view may or may not be accessible. While we can see the output of the data preparation, in this view we also take some other actions, such as creating analytical objects such as calculated tables, calculated columns, and measures, or copying data from tables.
Note
All objects we create in DAX are a part of our data model.
The following screenshot shows the Data view in Power BI Desktop when the storage mode of the table is set to Import:
Figure 1.4 – Data view; storage mode: Import
The Data view tab does not show the underlying data if the table only shows the data when the storage mode is set to Import. If the storage mode is set to DirectQuery, the data will not be shown in the Data view:
Figure 1.5 – Data view; storage mode: DirectQuery
The Model view
As its names implies, the Model view is where we stitch all the pieces together. Not only can we visually see h...
