Cloud-based Big Data Solutions
Description
Design and implementation of scalable big data solutions on major cloud platforms including AWS, Microsoft Azure, and Google Cloud Platform with focus on managed services, cost optimization, and security.
Learning Objectives
Students will architect and deploy big data solutions on cloud platforms, utilize managed big data services for scalability and cost-effectiveness, implement cloud security and governance practices, optimize cloud resource utilization and costs, design hybrid and multi-cloud big data architectures, and manage cloud-based data pipelines and analytics workflows.
Topics (8)
Comprehensive AWS cloud services for big data including elastic compute, managed databases, streaming analytics, and data integration services.
Microsoft Azure cloud platform services for big data processing, analytics, and machine learning with enterprise integration and hybrid cloud capabilities.
Google Cloud Platform services optimized for big data analytics including serverless data warehouse, stream processing, and machine learning integration.
Security best practices and governance frameworks for protecting big data in cloud environments including regulatory compliance and risk management.
Cost management strategies and resource optimization techniques for running cost-effective big data operations in cloud environments while maintaining performance.
Modern serverless approaches to big data processing using cloud-native services that eliminate infrastructure management and provide automatic scaling.
Workflow orchestration and automation for complex big data pipelines using cloud-native services to ensure reliability, scalability, and maintainability of data processing workflows.
Advanced cloud architecture patterns for big data that leverage multiple cloud providers and hybrid deployments for flexibility, vendor independence, and risk mitigation.