Technical Theory

Spanner + BigQuery: Real-Time Fraud Defense Shield  |  Google Codelabs

Executive Summary

This codelab guides you through building a real-time fraud detection system using Google Cloud Spanner and BigQuery. It focuses on leveraging Spanner's low-latency transactions and BigQuery's analytical capabilities to identify and respond to fraudulent activities in real time. This lab is targeted toward data engineers, database administrators, and developers interested in building scalable and robust fraud detection systems.

terminal
Interactive Lab

This codelab guides you through building a real-time fraud detection system using Google Cloud Spanner and BigQuery. It focuses on leveraging Spanner's low-latency transactions and BigQuery's analytical capabilities to identify and respond to fraudulent activities in real time. This lab is targeted toward data engineers, database administrators, and developers interested in building scalable and robust fraud detection systems.

Launch Codelab —>

Technical Breakdown

Category Technology Experience Resources
Database Google Cloud Spanner 4 / 5 Documentation
Data Warehousing Google BigQuery 4 / 5 Documentation
Cloud Computing Google Cloud 3 / 5 Documentation
Data Streaming Spanner Change Streams 4 / 5 Documentation
Programming Language SQL 3 / 5 Documentation

Learning Objectives

  • Build a real-time fraud detection system using Google Cloud Spanner and BigQuery.
  • Implement change streams in Spanner to feed data into BigQuery.
  • Analyze data in BigQuery to identify and respond to fraudulent activities.

Key Learning Points

  • Understand how to leverage Spanner's low-latency transactions for real-time fraud detection.
  • Learn to use BigQuery for analyzing large datasets and identifying fraud patterns.
  • Discover how to integrate Spanner and BigQuery to create a comprehensive fraud defense shield.

Core Skills Gained

  • Database Concepts
  • Cloud Computing
  • Data Analysis
  • SQL

Next Topic