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