Serverless Data Processing: Building Elastic Pipelines
Build scalable data pipelines using serverless services. Learn how AWS Lambda, Azure Functions, and Cloud Functions integrate for cost-effective processing.
Build scalable data pipelines using serverless services. Learn how AWS Lambda, Azure Functions, and Cloud Functions integrate for cost-effective processing.
Master Slowly Changing Dimension techniques including Type 1, Type 2, and Type 3 for maintaining historical accuracy in data warehouses.
Explore snowflake schema design, where dimension tables are normalized into related sub-tables, reducing redundancy and enabling shared reference data.
Discover why star schema remains the dominant approach for analytical databases, how it enables fast queries, and when to use it versus alternatives.
Implement audit logging for compliance. Learn row-level change capture with triggers and CDC, log aggregation strategies, and retention policies.
Learn database backup strategies: full, incremental, and differential backups. Point-in-time recovery, WAL archiving, and RTO/RPO planning.
Learn how single-flight, request coalescing, and probabilistic early expiration prevent cache stampedes that can overwhelm your database.
Plan for growth before you hit walls. This guide covers growth forecasting, compute and storage sizing, IOPS requirements, and cloud vs on-prem decisions.
Cassandra and HBase data storage explained. Learn partition key design, column families, time-series modeling, and consistency tradeoffs.
Learn connection pool sizing, HikariCP, pgBouncer, and ProxySQL, timeout settings, idle management, and when pooling helps or hurts performance.