Power BI is best known for the impressive data visualizations and dashboard capabilities it has.  However, before you can begin building reports, you first need to connect to the necessary data sources. Within the Power BI Desktop, a developer has more than 80 unique data connectors to choose from, ranging from traditional file types, database engines, big data solutions, cloud sources, data stored on a web page, and other SaaS providers. This book will not cover all 80 connectors that are available, but it will highlight some of the most popular.

When establishing a connection to a data source, you may be presented with one of three different options on how your data should be treated: Import, DirectQuery, or Live Connection. This section will focus specifically on the Import option.

Choosing to import data, which is the most common option, and default behavior, means that Power BI will physically extract rows of data from the selected source and store it in an in-memory storage engine within Power BI. The Power BI Desktop uses a special method for storing data, known as xVelocity, which is an in-memory technology that not only increases the performance of your query results but can also highly compress the amount of space taken up by your Power BI solution. In some cases, the compression that takes place can even lower the disk space required up to one-tenth of the original data source size. The xVelocity engine uses a local unseen instance of SQL Server Analysis Services (SSAS) to provide these in-memory capabilities. 

There are consequences to using the import option within Power BI that you should also consider. These consequences will be discussed later in this chapter, but as you read on, consider the following:

• How does data that has been imported into Power BI get updated?
• What if I need a dashboard to show near real-time analytics?
• How much data can really be imported into an in-memory storage system?