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

Algorithms used for forecasting

To properly make use of a machine learning technique such as forecasting, we need to understand how it works. Just making sure we have time-series data is not enough to get accurate predictions in Power BI. We need to understand the limitations and possibilities of the forecasting feature in Power BI to ensure that our results make sense. We'll first discuss how forecasting can be calculated, after which we will describe when we should use this feature in Power BI, based on the limitations and possibilities the underlying technique gives us.

The reason why some are skeptical of using an out-of-the-box feature such as forecasting in Power BI is because it is unclear what is actually happening under the hood. This kind of feature is often described as a black-box model – we can't see how the model is trained and how it creates predictions. Unfortunately, this is the intellectual property of Power BI and Microsoft and is, therefore,...