Book Image

Microsoft Power BI Data Analyst Certification Guide

By : Orrin Edenfield, Edward Corcoran
5 (1)
Book Image

Microsoft Power BI Data Analyst Certification Guide

5 (1)
By: Orrin Edenfield, Edward Corcoran

Overview of this book

Microsoft Power BI enables organizations to create a data-driven culture with business intelligence for all. This guide to achieving the Microsoft Power BI Data Analyst Associate certification will help you take control of your organization's data and pass the exam with confidence. From getting started with Power BI to connecting to data sources, including files, databases, cloud services, and SaaS providers, to using Power BI’s built-in tools to build data models and produce visualizations, this book will walk you through everything from setup to preparing for the certification exam. Throughout the chapters, you'll get detailed explanations and learn how to analyze your data, prepare it for consumption by business users, and maintain an enterprise environment in a secure and efficient way. By the end of this book, you'll be able to create and maintain robust reports and dashboards, enabling you to manage a data-driven enterprise, and be ready to take the PL-300 exam with confidence.
Table of Contents (25 chapters)
1
Part 1 – Preparing the Data
6
Part 2 – Modeling the Data
11
Part 3 – Visualizing the Data
15
Part 4 – Analyzing the Data
18
Part 5 – Deploying and Maintaining Deliverables
21
Part 6 – Practice Exams

Interrogating data statistics

Knowing how your data is distributed within a column can be extremely helpful. It can tell you a large amount of information in a simple, easy-to-understand format. In the Power Query Editor, there are two ways to see summarized data on a column: Column distribution and Column profile.

Column distribution

Column distribution generates a bar chart for the data in the column. This is particularly good for categorical data, such as countries, market segment, or payment type, for example. Below the bar chart, there will be two numbers, a count of distinct values in the column, including duplicates and nulls, and a count of how many values are unique.

As you can see from the following screenshot, this works better for categorical data than for continuous numbers:

Figure 3.7 – Power Query Editor displaying how data is distributed

Test Tip

Look for weird or unexpected distributions of your data. If you only have five...