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

Optimizing data in the model

We've covered, in previous chapters, how Power BI supports directly connecting to a data store, such as connecting to an Enterprise Data Warehouse (EDW) that has billions of records and years of sales history. When configured with DirectQuery performance, Power BI becomes dependent upon not only the calculations and rendering of visuals in the report but also the performance of the underlying data store. If the EDW takes a long time to query, then the Power BI report that uses the query will also take a long time.

To help, Power BI also supports importing data, which reduces the performance dependency on the underlying data store to increase the performance of report visuals. Data imported into the Power BI data model is stored both in memory and on disk using the VertiPaq Storage Engine (SE). VertiPaq will compress data, sometimes by as much as 10x, so even with limitations on the amount of data imported, it's often able to store large datasets...