Book Image

Artificial Intelligence with Power BI

By : Mary-Jo Diepeveen
Book Image

Artificial Intelligence with Power BI

By: Mary-Jo Diepeveen

Overview of this book

The artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data. This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data. You’ll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you’ll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you’ll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you’ll work through principles such as privacy, fairness, and transparency to use AI responsibly. By the end of this book, you’ll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI.
Table of Contents (18 chapters)
1
Part 1: AI Fundamentals
5
Part 2: Out-of-the-Box AI Features
13
Part 3: Create Your Own Models

Using visuals to explore your data

As a data analyst, you should be familiar with visualizing data. You use Power BI to make sure insights from the data are easily conveyed to your audience through visuals. The same visuals can also help you to understand the content and shape of your data.

First, we'll focus on the standard visualizations you can use in Power BI to explore your data, then we'll see how we can use Python in combination with the matplotlib library to create more customized visuals that we can add to our reports.

Line charts

One of the most basic charts we can create is a line chart. This is commonly used for showing how data changes over time to get insights into different trends.

To create a line chart, start in the Report view. We want to compare the Life Ladder score across the 3 years, so proceed as follows:

  1. Select Line chart from the Visualizations pane.
  2. Expand the world-happiness-report query in the Fields pane.
  3. Drag...