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

What this book covers

Chapter 1, Introducing AI in Power BI, introduces basic concepts associated with AI and Power BI.

Chapter 2, Exploring Data in Power BI, introduces some Power BI features to explore data as is often done in data science.

Chapter 3, Data Preparation, introduces some data requirements when implementing AI and how those requirements can be met within Power BI.

Chapter 4, Forecasting Time-Series Data, introduces forecasting as a data science method and how to use the built-in forecasting feature in Power BI.

Chapter 5, Detecting Anomalies in Your Data Using Power BI, introduces anomaly detection as a data science method and how to use the built-in anomaly detection feature in Power BI.

Chapter 6, Using Natural Language to Explore Data with the Q&A Visual, introduces natural language querying and how to use the built-in Q&A visual in Power BI.

Chapter 7, Using Cognitive Services, goes through the various AI models offered through Azure Cognitive Services and how they can be of use.

Chapter 8, Integrating Natural Language Understanding with Power BI, further explores Cognitive Services for Language and how to apply its models in Power BI.

Chapter 9, Integrating an Interactive Question and Answering App into Power BI, focuses on one of the Cognitive Services for Language models and how you can create a power app to create an interactive Q&A visual in Power BI.

Chapter 10, Getting Insights from Images with Computer Vision, further explores Cognitive Services for Vision and how to apply its models in Power BI.

Chapter 11, Using Automated Machine Learning with Azure and Power BI, introduces Azure Machine Learning and how to use its automated machine learning feature to quickly train multiple models. The best-performing model will be integrated with Power BI.

Chapter 12, Training a Model with Azure Machine Learning, covers how to train your own model in Azure Machine Learning, and how to integrate a model with Power BI.

Chapter 13, Responsible AI, discusses important considerations when working with AI to ensure its fair and responsible use.