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 sensitivity labels

As part of the holistic data protection capabilities, Power BI includes integration with Microsoft Information Protection (MIP). MIP provides sensitivity labels as a way of making it easy for users to classify critical content and data while not making this a burden for the user or restricting collaboration.

Sensitivity labels allow users to classify datasets, reports, dashboards, and dataflows as having a specific sensitivity so that data can be protected. For example, some data used in Power BI reports might be publicly accessible data, and this feature allows those datasets to be labeled as such. In the same way, internal sales data might need to be protected and labeled as confidential; when this happens, the data is protected by the service from being accessed by those who do not have permission to access data labeled confidential. It can also enforce encryption, restrict forwarding, and, in some cases, printing as well.

In Power BI, sensitivity...