Graph-Powered Analytics and Machine Learning with Tigergraph: Driving Business Outcomes with Connected Data

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, Xinyu Chan, and Gaurav Deshpande from TigerGraph 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.

• Use graph thinking to connect, analyze, and learn from data for advanced analytics and machine learning
• Learn how graph analytics and machine learning can deliver key business insights and outcomes
• Use five core categories of graph algorithms to drive advanced analytics and machine learning
• Deliver a real-time 360-degree view of core business entities, including customer, product, service, supplier, and citizen
• Discover insights from connected data through machine learning and advanced analytics

隨著圖形資料庫的快速崛起，組織現在正在實施先進的分析和機器學習解決方案來推動業務成果。這本實用指南向數據科學家、數據工程師、架構師和業務分析師展示了如何使用TigerGraph這一領先的圖形資料庫模型入門。

您將探索一種從連接資料中獲取價值的三階段方法：連接、分析和學習。TigerGraph的Victor Lee、Xinyu Chan和Gaurav Deshpande提供了幾個涵蓋當代業務需求的實際用例。通過使用TigerGraph Cloud進行實踐練習，您將迅速熟練設計和管理組織的先進分析和機器學習解決方案。

本書的重點內容包括：
- 使用圖形思維來連接、分析和學習數據，以進行先進的分析和機器學習
- 了解圖形分析和機器學習如何提供關鍵的業務洞察和成果
- 使用五個核心類別的圖形算法來推動先進的分析和機器學習
- 提供關鍵業務實體（包括客戶、產品、服務、供應商和公民）的實時360度視圖
- 通過機器學習和先進分析從連接資料中發現洞察

這本書將幫助您快速掌握使用TigerGraph設計和管理組織的先進分析和機器學習解決方案的能力。