Using a Date Dimension in any BI solution is a must to do. Not only because users might want to do slice and dice data by different date categories such as year, half year, quarter, month, week, fiscal categories. But also because sometimes you need to do analysis based on public holidays. Because Power Query can fetch public holidays live from a web query so it is a great tool for building a date dimension. In this lesson you learn how Power Query used for generating a date dimension with public holiday fetched live.
A reliable solution in Power BI should have a robust error handling implemented. Fortunately Power Query has the structure for implementing error handling. In this lesson you will learn how easy is to implement error handling in an example custom function.
Generators create lists, and leveraging EACH singleton function besides a generator enables us to loop through the list and do data transformation per each item in the list. This method is a good way of implementing loop structure in Power Query. You will learn through an example of custom function how generators and EACH function used.
Custom Functions improves the script. Custom function increases consistency of the code, and reduces redundancy. Power Query enables you to write your own custom code, and re-use it in your Power BI application as many times as you want. In this less you learn how to create a custom function through demos and examples.
Power Query is a functional language. Knowing functions is your best helper when you work with a functional language. Fortunately Power Query both in Excel and Power BI can use shared keyword to reveal a document library of all functions. In this lesson you learn how to use #shared keyword.
Power Query Formula Language is the code behind the scene for all Power Query operations. Anything that we do in Get Data & Transform graphical user interface will be converted to a script in a language informally named M (or Power Query Formula Language). This formula Language is much more powerful than graphical interface. There are some functions available in M which is not available in GUI. In this lesson you will learn basics about this scripting language.
Excel plays an important role as one of the data sources for Power BI. There are some tips to consider before using Excel as a source in Power BI. In this video you will learn which parts of Excel can be imported and which parts will be ignored. You will also learn how to Import an existing Power Pivot model into Power BI Desktop.
Best way to get started with Power Query is through a demo. In this section you will see a demo of getting data of best seller movies from Box Office Mojo. You will see how data will be fetched from web, and you will learn how to apply data transformation through graphical user interface of Power Query. In this demo you will also learn how this data can be combined with another data source, and the result of that be visualized in Power BI Desktop.
When you get data in Power BI you actually use Power Query Component. In this chapter you will learn about What Power Query is, and what are different types of sources that Power Query can connect. Power Query has also great list of transformations that can be applied on the data set as well (which will be covered in next chapter), and the Power Query formula language M can be used for complex and powerful data transformation situations (will be covered in a chapter after). In this section you will read an introduction to Power Query. You will learn; What Power Query is? What types of works can be done with Power Query? What are requirements to run Power Query? What are features of Power Query Premium?
In this section I will go through below modules with you; Open and Modify Reports in Power BI Website Building Dashboards Sharing Power Q&A Power BI Mobile App