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 3: Profiling the Data

After connecting to data and getting it into Power BI, your next step will be to profile your data, or as data scientists and statisticians call it, performing exploratory data analysis. This is the process of getting to know your data. One of the worst things you can do is to create reports without knowing how the underlying data is structured. This is particularly true of data you work with all the time. It's often a great idea to step back and really look at the data you are working with to make sure you understand what is there and what isn't.

If you have null values in a column of data, how will you handle them? If you are only getting 100 rows when you expected 10,000, what will you do?

Power BI loves working with date fields, but what if your dates are coming in as text? Or as a number?

You will have to learn how to identify these problems and correct them. The PL-300 exam may test you on how to identify and fix these problems...