Power BI is Microsoft’s amazing data preparation and visualization tool. It is seemingly so simple, but looks can be deceiving. Hidden beneath an easy tool are amazing abilities to clean data, organize data, calculate data, and present that data in a logical and simple matter. In this class, we seek to unlock all the power and flexibility that Power BI has to offer.
Power BI is actually three separate products, Power BI Desktop, Power BI Services, and Power BI Mobile. This class is a comprehensive look at all the available components. We also cover the data gateway service and the stand-alone report server.
This course uses real-world examples of common data patterns to help users choose the correct visualization for the right problem. It also covers good dashboard design and navigation practices, so their products are incredibly usable.
Power BI uses two different languages: DAX and R. We’ll introduce the students to creating DAX expressions to clean and organize data and to create custom calculations. R is a great statistical language used by data scientists around the world. This course will have the student learn the basics of R using R Studio. Once that is covered, we’ll incorporate R visuals into our Power BI Dashboards.
Also covered is Power BI in Excel and all the neat data features available to us in Microsoft’s popular data analytics tool. Finally, we introduce Power Apps, an easy way to build applications using similar techniques to Power BI. Simple apps are sometimes needed by BI teams to input forecasting data, projections, and other user input.
Key Learning Areas
• Introducing the Power BI ecosystem
• Cleaning, prepping, and organization data models with Power BI Desktop
• Creating visualizations
• Using Time Intelligence
• Sharing Power BI data and visualizations with the Power BI Portal
• Beginning R
• Incorporating R into Power BI
• Beginning and Advanced DAX Expressions
• Deciding between DirectQuery and importing data
• Integrating and using Power BI with Excel
• Beginning Power Apps
In this module, we demo all the different components in the Power BI ecosystem. We show how all these components interact with each other, so the user can see the moving pieces and understand where the class will be taking them.
Prepping and Cleaning Data
Power BI has so many features to help you organize and prep data. In can convert data types, add columns, append queries together, merge queries (like a join), and combine files. In this section, we’ll explore all the things the Query Editor can do to bring in data from different sources and combine them for use across all your reports
Power BI’s Query Editor can do many things with data from different data sources. In this section, we’ll talk about proper data modeling techniques to keep the data model clear, concise, usable, and powerful. We’ll add a date table to introduce date calculations. We’ll create hierarchies to make exploring the data easier in our visualizations.
Introduction to DAX Expressions
DAX is the central expression language of Power BI. It is also used in Excel Power Pivot and SQL Server Analysis Services. In this section, we’ll create calculated columns, use conditional logic, and create calculated measures. We’ll also introduce time intelligence so we can compare values between time periods and more. We’ll also cover iterator functions, like SUMX.
Advanced DAX Expressions
In this section, we’ll kick our DAX usage up a notch and talk about the CALCULATE function. It’s a pretty complicated function for beginners, but you’ll soon see how indispensable this is. We’ll also use the FILTER context to build advanced metrics. Finally, we’ll explore how we can use DAX to implement granular security. We’ll also create many-to-many relationships, and look at data with mismatched granularity.
We just spent two days learning about data and we’re finally ready to create visualizations. If the data is ready, this is the easy and fun part. We’ll go through all the different visualizations available to us and choose the right ones for the right task. We’ll talk about fun things, like coloring, user navigation, clarity, and clutter.
Advanced Report Authoring
We will create dashboards that look great on the desktop and on mobile. We’ll add slices, analyze trends, and look at goal tracking. We’ll also import custom visuals. We’ll see the benefit of having a great data model when it comes to creating mapping visuals. We’ll use the hierarchies and date tables that we created.
In this section, we’ll explore all that the Power BI Service has to offer us. We’ll look at creating and sharing dashboards. We’ll setup a subscription and create alerts. We’ll use Power BI Q&A to easily answer questions we might have. We’ll also look at Power BI support for real-time dashboards. We’ll also look at local publishing and how we can use Power BI and SQL Server Reporting Services (SSRS) in the same portal.
Data and DirectQuery
Power BI gives us a lot of options to manage our data. We can import all the data into Power BI or we can use Direct Query mode. This section will provide guidance on when to use one over the other. We’ll also look at the Data Gateway, a neat tool that allows Power BI Services to load data from your internal servers. We’ll examine scheduling a data refresh.
Power BI with Excel
We can incorporate Excel with Power BI visuals. We’ll explore neat things we can do with that functionality. In addition, Excel has many of the tools that Power BI has, and we’ll examine porting our knowledge over to that tool.
Introduction to Power Apps
Power Apps is a service that is similar to Power BI. It allows us to create input forms that work on mobile. We can create these forms easily and with no coding. We can update content that we later use in reporting.
R is a language for statistical computing and graphics. R provides a wide variety of statistical and graphical techniques. It is used by scientists and business professionals around the world. In this section, we’ll introduce one of the most popular R packages, ggplot2. We’ll look at creating some advanced visualizations, like time-series analysis and clustering. We’ll learn about using RStudio as an IDE for creating R visuals.
Incorporating R into Power BI
We’ll take what we learned in the last module and import it into Power BI. Combining R and Power BI will allow use to better clean and visualize our data. It’s a powerful combination that unlocks limitless functionality.
This class is for anyone who wants to use data to make decisions or help others make decisions. It’s for the data analyst, business person, scientist, developer, data engineer, or organizational leader who can commit themselves to learning new skills, trying new things, and unlocking the magic of data into their lives.
The expected audience for this course is business analysts and BI professionals that want to learn Power BI.