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

Summary

Power BI can help us to get quick insights into our data. One powerful out-of-the-box feature is anomaly detection. To use anomaly detection, we now know we need to have time-series data with enough data points and—optionally—some other attributes we want Power BI to use to explain any anomalies it may find. We learned that by plotting the metric we want to monitor in a line chart with a date field on the x axis, we can enable anomaly detection to find any anomalies. Some anomalies may be obvious, and some may be very subtle. For whichever anomaly Power BI finds, we can explore any possible explanations based on the attributes we included in our dataset to get insights into why these anomalies have occurred. Remember that domain knowledge is still needed to validate these insights and correctly interpret them. In the next chapter, we will look at another out-of-the-box feature: the question-and-answer (Q&A) visual. This visual not only helps you but actually...