Book Image

Learn Power BI - Second Edition

By : Gregory Deckler
5 (1)
Book Image

Learn Power BI - Second Edition

5 (1)
By: Gregory Deckler

Overview of this book

To succeed in today's transforming business world, organizations need business intelligence capabilities to make smarter decisions faster than ever before. This updated second edition of Learn Power BI takes you on a journey of data exploration and discovery, using Microsoft Power BI to ingest, cleanse, and organize data in order to unlock key business insights that can then be shared with others. This newly revised and expanded edition of Learn Power BI covers all of the latest features and interface changes and takes you through the fundamentals of business intelligence projects, how to deploy, adopt, and govern Power BI within your organization, and how to leverage your knowledge in the marketplace and broader ecosystem that is Power BI. As you progress, you will learn how to ingest, cleanse, and transform your data into stunning visualizations, reports, and dashboards that speak to business decision-makers. By the end of this Power BI book, you will be fully prepared to be the data analysis hero of your organization – or even start a new career as a business intelligence professional.
Table of Contents (19 chapters)
1
Section 1:The Basics
4
Section 2:The Desktop
10
Section 3:The Service
15
Section 4:The Future

Summary

In this chapter, we explored the Power Query Editor, the powerful sub-application that's used to ingest and shape data through the creation of queries. Queries are a series of recorded steps for connecting to and transforming data. We connected to multiple data files and learned how to clean up and transform the data to support further analysis. Next, we learned about more advanced operations such as how to merge, copy, and append queries. Finally, we explored some built-in data quality and profiling tools that summarize, visualize, and provide statistical information about the data we are ingesting.

In the next chapter, we will build a data model by connecting the tables created by these queries to one another via relationships. We will also build the necessary calculations that will complete our model.