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The data source is the point from which the data has been retrieved. It can be anything like files in VARIOUS formats (.xlsx, .csv, .pbix, .xml, .txt etc), databases (SQL database, SQL Data WAREHOUSE, Spark on Azure HDInsight), or FORM content packets like Google Analytics or Twilio.

POWER BI is available in various formats:

• Power BI desktop: For the desktop version
• Power BI mobile app: For using the visualizations on mobile OS and SHARE it
• Power BI services: For ONLINE SAAS

In power BI, you have various kinds of views viz:

• DATA View: Curating, exploring, and viewing data TABLES in the data set. Unlike, Power Query editor, with data view, you are LOOKING at the data after it has been fed to the model.
• Model View: This view shows you all the tables along with their COMPLEX relationships. With this, you can break these complex models into simplified diagrams or set properties for them at once.
• Report View: The report view displays the tables in an interactive format to simplify data analysis. You can create N number of reports, provide visualizations, merge them, or apply any such functionality.

Primarily, Power BI has TWO sources to store data:

Azure BLOB Storage: When users upload the data, it gets stored here.
Azure SQL Database: All the metadata and system artifacts are stored here.

They are stored as EITHER FACT tables or dimensional tables.

To access the Power BI features, visualize data, or model them to create REPORTS, you can simply download a desktop version of Power BI. With the desktop version, you can extract data from VARIOUS data sources, transform them, create visuals or reports, and share them using Power BI services.

The three major CONNECTIVITY modes in Power BI are:

Direct Query: The method allows direct connection to the Power BI model. The data doesn’t get stored in Power BI. Interestingly, Power BI will only store the metadata of the data tables involved and not the actual data. The supported sources of data query are:

• Amazon Redshift
• Azure HDInsight Spark (Beta)
• Azure SQL Database
• Azure SQL Data Warehouse
• IBM Netezza (Beta)
• Impala (version 2.x)
• Oracle Database (version 12 and above)
• SAP BUSINESS Warehouse (Beta)
• SAP HANA
• Snowflake
• Spark (Beta) (version 0.9 and above)
• SQL Server
• Teradata Database

Live Connection: Live connection is analogous to the direct query method as it doesn’t store any data in Power BI either. But opposed to the direct query method, it is a direct connection to the analysis services model. Also, the supported data sources with live connection method are limited:

• SQL Server Analysis Services (SSAS) Tabular
• SQL Server Analysis Services (SSAS) Multi-Dimensional
• Power BI Service

Import Data (Scheduled REFRESH): By choosing this method, you upload the data into Power BI. Uploading data on Power BI means consuming the memory space of your Power BI desktop. If it is on the website, it consumes the space of the Power BI cloud machine. Even though it is the fastest method, the MAXIMUM size of the file to be uploaded cannot exceed 1 GB until and unless you have Power BI premium (then you have 50 GB at the expense). 

But which model to choose when depends on your use and purpose.

Four main refresh options are available in Power BI:

• Package/OneDrive refresh: This synchronizes Power BI desktop or EXCEL file between the Power BI service and OneDrive
• Data/Model refresh: This means scheduling the data import from all the sources BASED on EITHER refresh schedule or on-demand. 
• Tile refresh: Refresh the tiles’ cache on the dashboard every time the data changes.
• Visual container refresh: Update the REPORTS’ VISUALS and visual container once the data changes.

Power BI is an amalgamation of these major components:

• Power Query (for data mash-up and TRANSFORMATION): You can use this to extract data from various databases (like SQL Server, MySql, and many others ) and to delete a chunk of data from various sources.
• Power Pivot (for tabular data modeling): It is a data modeling engine that uses a functional language called Data ANALYSIS EXPRESSION (DAX) to perform the calculations. Also, creates a relationship between various tables to be viewed as pivot tables.
• Power View (for viewing data visualizations): The view provides an interactive display of various data sources to extract metadata for proper data analysis.
• Power BI DESKTOP (a companion development tool): Power Desktop is an AGGREGATED tool of Power Query, Power View, and Power Pivot. Create advanced queries, models, and reports using the desktop tool.
• Power BI Mobile (for Android, iOS, Windows phones): It gives an interactive display of the dashboards from the site onto these OS, effortlessly.
• Power Map (3D geo-spatial data visualization).
• Power Q&A (for natural language Q&A).

Power BI is a strong business analytical tool that creates USEFUL insights and reports by COLLATING data from unrelated sources. This data can be extracted from any source like Microsoft EXCEL or hybrid data warehouses. Power BI drives an extreme level of utility and purpose using interactive GRAPHICAL INTERFACE and visualizations. You can create reports using the Excel BI toolkit and share them on-cloud with your colleagues.