Google Data & AI Boot-Kon - FraudFix Use Case

Welcome to the Google Data & AI Boot-Kon repository. This repository contains user manuals links in DOC format for the FraudFix use case.

Caution

CAUTION: This lab is for educational purposes only and should be used with caution in production environments. Google Cloud Platform (GCP) products are changing frequently, and screenshots and instructions might become inaccurate over time. Always refer to the latest GCP documentation for the most up-to-date information.

---

Contents

• [Main Github] Boot-Kon Data & AI Event
• Understand the FraudFix Use Case
• [Hands-on Lab - 1] Setup your environment_ Notebooks & IAM
• [Hands-on Lab - 2] Data Ingestion with Dataproc , BigLake & PubSub
• [Hands-on Lab - 3] ELT & Lakehouse _ BigQuery, Dataform, LLM for sentiment analysis
• [Hands-on Lab - 4] ML Operations with Vertex AI
• [Hands-on Lab - 5] Data Governance with Dataplex
• [Hands-on Lab - 6] Data Sharing with Analytics Hub
• [Hands-on Lab - 7] Data Canvas & Looker Studio
• Use Case Closure: Architecture challenge and retrospective

Getting Started

1. Check the readme file listed in the Contents section.
2. Click on the links to view each lab's DOC file.
3. Follow the instructions.

Recommended Code Editors

To make the most out of the BootKon event, we suggest using one of these code editors for easy code editing and environment customization:

• Mac & Windows:

  • Visual Studio Code (VS Code)
  • Sublime Text
  • Atom
  • Notepad++

• Google Chromebooks:

  • Visual Studio Code (VS Code)
  • StackBlitz
  • Gitpod

Feedback

If you have any feedback or issues, please open an issue in this repository or contact the repository maintainers.

---

Thank you for participating in the Google Data & AI Boot-Kon!

Author: Wissem Khlifi

Linkedin : https://www.linkedin.com/in/orawiss/