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

Using anomaly detection

One of the great ways to find outliers is using the built-in Find anomalies tool in the Analysis pane of a visualization in Power BI. This feature of Power BI uses Artificial Intelligence (AI) capabilities to identify which data points are most different from other values in your data. The purpose of this feature is to help with analyzing the data so that action can be taken either against the data before business decisions are made or to help report consumers better understand the data and make informed business decisions.

To use this capability, you need to be using a supported visual (such as a line or scatter chart) and only one field on the y axis or values. This feature is being improved; so, at the time of writing, this was the requirement.

Figure 13.2 – Automated anomaly detection is built into some visualizations

Once this has been enabled, you can see the outliers identified with a gray dot. These are anomalies that...