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)
Part 1: AI Fundamentals
Part 2: Out-of-the-Box AI Features
Part 3: Create Your Own Models

Understanding the logic behind anomaly detection

The algorithm behind the anomaly detection feature in Power BI has been developed by Microsoft and is designed for real-time time-series data in many different applications. The purpose of this section is not to go over all technical details but instead to keep it pragmatic. In this section, we will explore the key considerations of this algorithm that help us understand how to use the feature in Power BI appropriately. For more in-depth information, you can read the paper Time-Series Anomaly Detection Service at Microsoft by Ren et al., 2019.

The algorithms behind Microsoft's anomaly detection feature

First of all, the algorithm created by Microsoft is a combination of two methods and is referred to as SR-CNN. SR stands for Spectral Residual and CNN stands for Convolutional Neural Network. Both of these deep learning (DL) methods are most often used for analyzing images, and it's the combination of these two techniques...