Explains database denormalization: when to flatten data for faster analytics queries and when to avoid it.
An introduction to data modeling concepts, covering OLTP vs OLAP systems, normalization, and common schema designs for data engineering.
Explores the core reasons for using Change Data Capture (CDC) to extract data from operational databases for analytics and other applications.
Explains the fundamentals of distributed consensus algorithms like Raft, used in transactional databases and systems like Kubernetes.
Compares columnar vs. row-based data structures, explaining their optimal use in OLAP and OLTP systems for performance and scalability.
An introduction to modern data systems, explaining OLTP, OLAP, data warehouses, data lakes, and the roles of data engineers, analysts, and scientists.
Explains the differences between batch and streaming data processing, covering OLTP, OLAP, and ETL concepts for data engineers.
Analysis of HP's marketing claims against Oracle Exadata, focusing on technical FUD and balanced system design for data warehousing.
