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

Fixing the structure of your data

The data you connect to in Power BI will appear in tabular format. For example, when we import data from an Excel file into Power BI, we can view it as a table with column headers and row values. Based on the data detected and the information gathered from the data source, Power BI will then also assign a data type to each column. You can change the data type for each column afterward, and this is necessary for some features you may want to use. To calculate certain summary statistics such as averages, as we have seen in Chapter 2, Exploring Data in Power BI, we need a column to have numerical data as the data type. To do time-series forecasting, as we will see in Chapter 4, Forecasting Time-Series Data, we need a column that has date/time as a data type.

In the following figure, you can see the design of a table as presented in Power BI and the important features:

Figure 3.1 – Design of a table in Power BI

As shown...