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

Query performance tuning

When considering optimizing the performance of Power BI queries, there are a few places to start, and the recommendation is to look at each as a layer of performance tuning to undertake. These layers include reducing the size of the data, optimizing DirectQuery (when used), and optimizing composite models (when used).

Reducing the data size

This technique is the idea of limiting the amount of data that Power BI needs to work with to only what is needed for the report. For example, if the sales database being used as the source for the report contains sales data for 70 countries but there is only a need to report sales for 5 countries, then it makes sense to only use data for the 5 needed countries. This can be accomplished when connecting to the source database and using a WHERE clause that limits the data to only the rows for the needed countries.

While this technique works well with rows of data, it can be applied to columns also. It's not...