Preface
As an experienced BI professional, you may have, at one time, considered your skills irreplaceable. However, while you were tirelessly building the most elegant data warehouse solutions, Microsoft was busy building a new suite of self-service business intelligence and analytics tools called Power BI. Quickly, Power BI has become one of the most popular tools in the market, and users are looking to you for advice on how they should implement best practices and scale their own usage of the tool. While your corporate BI solutions will always be the gold standard for your company's enterprise data strategy, you can no longer ignore your company's hunger for self-server data wrangling.
In this book, you will learn how to bridge the gap of your existing corporate BI skillset into what's possible with Power BI. You will understand how to connect to data sources using both import and direct query options. You will then learn how to effectively use the Power BI Query Editor to perform transformations and data-cleansing processes to your data. This will include using R script and advanced M query transforms. Next, you will learn how to properly design your data model to navigate table relationships and use DAX formulas to enhance its usability. Visualizing your data is another key element of this book, as you will learn proper data visualization styles and enhanced digital storytelling techniques. Finally, by the end of this book, you will understand how to administer your company's Power BI environment so that deployment can be made seamless, data refreshes can run properly, and security can be fully implemented.
Who this book is for
This book is intended for business intelligence professionals who have experience with traditional enterprise BI tools in the past and now need a guide to jumpstart their knowledge of Power BI. Individuals new to business intelligence will also gain a lot from reading this book, but knowledge of some industry terminology will be assumed. Concepts covered in this book can also be helpful for BI managers beginning their companies' self-service BI implementation. Prior knowledge of Power BI is helpful but certainly not required for this book.
What this book covers
Chapter 1, Getting Started with Importing Data, begins by getting the audience oriented with the Power BI Desktop. Next, they will learn how to connect to various common data sources in Power BI. Once a data source is chosen, the options within will be explored, including the choice between data import, direct query, and live connection.
Chapter 2, Data Transformation Strategies, explores the capabilities of the Power Query Editor inside the Power BI Desktop. Using this Power BI Query Editor, the reader will first learn how to do basic transformations, and they will quickly learn more advanced data-cleansing practices. By the end of this chapter, the audience will know how to combine queries, use parameters, and read and write basic M queries.
Chapter 3, Building the Data Model, discusses one of the most critical parts of building a successful Power BI solution—designing an effective data model. In this chapter, readers will learn that while designing a data model, they are really setting themselves up for success when it comes to building reports. Specifically, this chapter will teach the audience how to establish relationships between tables, how to deal with complex relationship designs, and how to implement usability enhancements for the report consumers.
Chapter 4, Leveraging DAX, teaches that the Data Analysis Expression (DAX) language within Power BI is critical to building data models that are valuable to data consumers. While DAX may be intimidating at first, readers will quickly learn that its roots come from the Excel formula engine. This can be helpful at first, but as you find the need to develop more and more complex calculations, readers will learn that having a background in Excel formulas will only take them so far. This chapter will start with an understanding of basic DAX concepts but quickly accelerate into more complex ideas, such as like Time Intelligence and Filter Context.
Chapter 5, Visualizing Data, describes how to take a finely tuned data model and build reports that properly deliver a message that clearly and concisely tells a story about the data.
Chapter 6, Digital Storytelling with Power BI, covers the capability Power BI has to be much more than just a simple drag-and-drop reporting tool. Using the storytelling features of Drillthrough Filters, Bookmarks, and the Selection pane, you have the ability to design reports that not only display data but also tell engaging stories that make your users crave for more.
Chapter 7, Using a Cloud Deployment with the Power BI Service, examines deploying your solution to the Power BI Service to share what you've developed with your organization. Once deployed, you can build dashboards, share them with others, and schedule data refreshes. This chapter will cover the essential skills a BI professional would need to know to top off a Power BI solution they have developed.
Chapter 8, On-Premises Solutions with Power BI Report Server, explores how many organizations have decided that they are not yet ready to move to the cloud. Using the Power BI Report Server cloud, wary organizations get the benefit of Power BI reports without compromising their feelings about the cloud. This chapter will cover deploying to the Power BI Report Server cloud, sharing reports with others, and updating data.
To get the most out of this book
After downloading and installing the Power BI Desktop, you will be able to follow the majority of the examples in this book. By subscribing to the Power BI Pro license, you can follow all examples in this book. There are also supplementary files you can download to follow the book examples.
Download the example code files
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Conventions used
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