Data Architecture: Designing for Scale, Speed, and Efficiency | Architect

Data Architecture: Designing for Scale, Speed, and Efficiency
Stop fixing slow databases. Start architecting data pipelines that scale effortlessly.In modern computer science, a system is only as fast as its data layer. Simply writing clean code isn’t enough if your underlying data architecture suffers from high latency, redundant storage, or poor scaling boundaries. This course bridges the gap between foundational data structures and enterprise-level system design.You will learn how to evaluate tradeoffs between storage efficiency, computational complexity, and retrieval speed to design world-class data systems.🧭 What You Will Master:The Latency Hierarchy: How physical memory, SSDs, and network architecture dictate data placement strategies.Storage Paradigms: Mastering Row-oriented vs. Columnar storage models and when to deploy them (OLTP vs. OLAP).Caching & Indexing Geometry: Deep dive into B-Trees, LSM-Trees, and distributed caching topologies to accelerate data access paths.Distributed Data Patterns: Partitioning, sharding, and managing data consistency models across distributed nodes ($CAP\ Theorem$).Modern Lakehouse Pipelines: Designing unified streaming and batch processing layers using modern file formats (Parquet, Avro).By the end of this course, you won't just know how to store data—you will possess the engineering intuition to select, design, and optimize the exact architecture your system needs to handle millions of requests per second.

Видео Data Architecture: Designing for Scale, Speed, and Efficiency | Architect канала Beyond School Skills