Data Modeling for Analytics: Optimize for Queries, Not Transactions
Explains why transactional data models are inefficient for analytics and how to design denormalized, query-optimized models for better performance.
Explains why transactional data models are inefficient for analytics and how to design denormalized, query-optimized models for better performance.
Explains database denormalization: when to flatten data for faster analytics queries and when to avoid it.
Learn five strategies for modeling one-to-many relationships in Amazon DynamoDB, including denormalization and composite keys.
A guide on using R and dplyr to denormalize and join datasets for analysis in Kibana/Elasticsearch, using a road accident data example.