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 2: Connecting to Data Sources

In most organizations, data tends to be stored in various data stores, such as filesystems, proprietary and open source databases, or even distributed filesystems for high-performance compute platforms. Often the data has meaning and is useful while being stored in the source systems, such as a transactional database that keeps track of sales from a group of point-of-sale systems. In this example, data is stored in a relational database that is tuned to keep track of each sale. For analytics purposes, we will likely want to use this data in concert with data from a separate system that tracks the inventory of items we have for sale. The inventory will likely be a different relational database, possibly from another technology vendor. To better understand whether we are stocking too many items (or not enough) for sale, we need to create a view of the data from both sales and inventory databases.

Over the past few decades, this has been the goal...