Why normalization matters Normalization reduces redundancy and enforces consistent, unambiguous data models so updates, inserts, and deletes don’t create contradictions. […]
Measure Query Performance Accurate measurement starts with repeatable, objective metrics: wall‑clock (elapsed) time, CPU time, logical and physical reads, rows
Design goals and constraints Design decisions should prioritize correctness and predictable performance. Enforce data integrity with appropriate types and database
Embedding fundamentals and intuition Embeddings turn text into numeric vectors so machines can reason about meaning: similar phrases map to
Define goals and success metrics Start by tying analytics objectives to concrete business outcomes: what decision will change, who will
Define quality metrics and thresholds Start by selecting a small set of measurable quality dimensions tied to business impact: accuracy
Analyze access patterns Start by instrumenting the database and application to collect query logs, latency percentiles, QPS, and resource metrics
Why Conversational AI Matters Conversational AI shifts interfaces from rigid menus to natural language, letting users complete tasks faster and
What is a CNN? A convolutional neural network is a specialized deep-learning model built to process images and other grid-like