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

Chapter 13: Performing Advanced Analysis

We have already covered how, as a report author, you can use features to enhance your reports for analytical insights, such as Q&A and exporting. In this chapter, you will closely examine your data and Power BI reports and then extract value with deeper analysis. You will learn how to get a statistical summary for your data, analyze time series data, and group and bin your data. You will also apply and perform advanced analytics on the report for deeper and more meaningful data insights.

In this chapter, we will cover the following:

  • Identifying outliers
  • Using anomaly detection
  • Conducting time series analysis
  • Using grouping and binning
  • Using the key influencers to explore dimensional variances
  • Using the decomposition tree visual to break down a measure
  • Applying AI insights

These are some of the more advanced features of Power BI. They allow you to become your own junior data scientist, granting you...