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

What this book covers

Chapter 1, Overview of Power BI and the PL-300 Exam, provides you with an overview of the Pl-300 exam and the value of the certification as well as Power BI.

Chapter 2, Connecting to Data Sources, prepares you for connecting to various data sources that can provide the raw data needed for use in downstream processes.

Chapter 3, Profiling the Data, helps you to understand the shape of data (columns, data types, and rows) as well as overall statistics (counts, mean, max, and min values) where appropriate. This will, in turn, allow you to understand what kind of cleansing and reshaping will be needed for this data to be valuable to the end analytics consumer.

Chapter 4, Cleaning, Transforming, and Shaping Data, showcases the capabilities of Power BI in being able to clean and transform data so that it can be trusted and is reliable to meet the required needs of the organization.

Chapter 5, Designing a Data Model, shows you how you can design data models depending on various use cases, and the various tools needed for the exam.

Chapter 6, Using Data Model Advanced Features, showcases the various advanced features that you can use for data models, including security and hierarchies.

Chapter 7, Creating Measures Using DAX, explores DAX and showcases how to use measures and columns using it.

Chapter 8, Optimizing Model Performance, covers the most important data model optimization methods. It is important for every Power BI solution to be optimized at every architectural layer and starting with an optimized data model is key to ensuring performance and maintainability.

Chapter 9, Creating Reports, starts with basic report creation and ends with advanced report capabilities, such as integration with other enterprise services.

Chapter 10, Creating Dashboards, walks you from creating your first dashboard to designing multiple dashboards with KPIs and tiles from paginated reports and optimizing dashboards for performance.

Chapter 11, Enhancing Reports, explores the capabilities that allow for tailoring reports to custom graphics, inclusive design, drillthrough reports allowing users to further explore data to gain insights, and also programmatic features that allow reports to behave similarly to applications.

Chapter 12, Exposing Insights from Data, covers tools and techniques in Power BI that enable users to expose insights from data. Tools such as slicers, top N analysis, statistical summaries, and quick insight tools allow users to take data from visuals in a report, complete some analysis, and draw conclusions from the reports. This is the essence of unlocking information from data.

Chapter 13, Performing Advanced Analysis, covers advanced analytics that are often used by data analysts or scientists that need to unlock a deeper understanding of data and the business processes behind data. This includes time series analysis, binning data, and detecting outliers. This chapter will introduce these concepts and show how users can use Power BI for these kinds of analyses.

Chapter 14, Managing Workspaces, explains what a workspace is, how to secure it, and how to use deployment pipelines so you can have separate development, test, and production environments. We will also cover monitoring your workspace to see who is doing what and when.

Chapter 15, Managing Datasets, starts by looking at refreshing datasets from both cloud-based and on-premises sources. Then, we'll move on to sharing our datasets and helping others to identify what's in them. We'll then talk about lineage, which allows you to see who is using your dataset and allows you to see what data your dataset depends on. Finally, we have a section on security. Topics covered will include Microsoft Information Protection, encryption, watermarking, and cloud app security.

Chapter 16, Practice Exams, covers the exam format and has various key questions, along with their answer keys, so that you can prepare yourself.