With the rapid rise of graph databases, organizations are now implementing advanced analytics and machine learning solutions to help drive business outcomes. This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available. You'll explore a three-stage approach to deriving value from connected data: connect, analyze, and learn. Victor Lee, Phuc Kien Nguyen, and Alexander Thomas present real use cases covering several contemporary business needs. By diving into hands-on exercises using TigerGraph Cloud, you'll quickly become proficient at designing and managing advanced analytics and machine learning solutions for your organization. The goal of this book is to introduce you to the concepts, techniques, and tools for graph data structures, graph analytics, and graph Machine Learning. When you’ve finished the book, we hope you’ll understand how graph analytics can be used to address a range of real-world problems.