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 basic statistical functions to enhance data

Like many programming languages DAX has built-in capabilities for statistical and aggregation functions, such as sum, count, and averages. If you've used these functions in Microsoft Excel, you will pick up how to use these functions quickly in DAX.

Often our reports use statistics to explain and explore our data. Statistics can show you how your data is distributed, explain trends, or identify outliers. Using statistics to summarize your data can provide a quick and easy way to not only describe your data but also help find new insights or heretofore undiscovered trends. We saw this in Chapter 3, when we used data profiling to help us understand our data in Power Query.

Generating a statistical summary can provide you with a high-level view of your data. The advantage of doing this in DAX over Power Query is that we can use the relationships in our model and generate statistics that cover more than one table. This will help...