Database and Storage Technologies
Description
Comprehensive understanding of cloud database services, storage solutions, data management strategies, and the differences between relational and NoSQL databases.
Learning Objectives
Learners will master various database technologies and storage solutions in cloud environments, understanding when to use relational vs NoSQL databases, implementing data backup and recovery strategies, and optimizing database performance for cloud workloads.
Topics (7)
Amazon Redshift, Azure Synapse Analytics, Google BigQuery, data lakes, ETL processes, data modeling, and analytics workload optimization in cloud environments.
Cloud RDS services, database migration, performance tuning, high availability configurations, read replicas, and managed database features across cloud platforms.
MongoDB, Cassandra, DynamoDB, Redis, Neo4j, and other NoSQL solutions, understanding CAP theorem, eventual consistency, and choosing appropriate NoSQL solutions for different scenarios.
Amazon S3, Azure Blob Storage, Google Cloud Storage, storage classes, lifecycle management, versioning, and integration with applications and content delivery networks.
Database performance monitoring, query optimization, indexing strategies, caching layers (Redis, Memcached), read replicas, sharding, and auto-scaling for databases.
Automated backup solutions, point-in-time recovery, cross-region replication, disaster recovery testing, RTO/RPO planning, and data archival strategies.
Migration assessment, database migration tools, minimal downtime migration strategies, legacy system modernization, and post-migration optimization techniques.