Argues against placing business logic in stored procedures, advocating for keeping it in the application layer for better maintainability and scalability.
Explains Slowly Changing Dimensions (SCD) types 1-3 for managing data history in data warehouses, with practical examples.
A comprehensive guide to data modeling, explaining its meaning, three abstraction levels, techniques, and importance for modern data systems.
Compares Star Schema and Snowflake Schema data models, explaining their structures, trade-offs, and when to use each for optimal data warehousing.
Explains the three levels of data modeling (conceptual, logical, physical) and their importance in database design.
Seven common data modeling mistakes that cause reporting errors and slow analytics, with practical solutions to avoid them.
Explains database denormalization: when to flatten data for faster analytics queries and when to avoid it.
Explores three techniques for implementing multitenancy in EF Core applications, focusing on tenant isolation strategies and context configuration.
A guide to implementing UUIDv7 in Python, Django, and PostgreSQL for better database performance and ordered identifiers.
Explores why coding is just one component of software engineering, highlighting system design, architecture, and the role of AI tools.
A monthly roundup of 78 curated links on data engineering, architecture, AI, and tech trends, with top picks highlighted.
An introduction to data modeling concepts, covering OLTP vs OLAP systems, normalization, and common schema designs for data engineering.
Explores the differences between event and entity data modeling, when to use each approach, and practical design considerations for structuring data effectively.
Discusses the pros and cons of soft deleting database records, including implementation, performance, and alternatives.
Compares columnar vs. row-based data structures, explaining their optimal use in OLAP and OLTP systems for performance and scalability.
Explains how to use Kahn's algorithm for topological sorting to detect cycles in graphs, with a practical example of managing employee hierarchies.
Explains how TigerBeetle, a database written in Zig, operates using only static memory allocation for predictability and performance.
A technique for future-proofing SQL code by intentionally adding errors to catch unexpected changes in data or logic.
An introductory guide to database fundamentals, covering data design, relationships, and types of databases for application development.
A guide to the three most critical DynamoDB limits: item size, query/scan page size, and partition throughput, and how they impact data modeling.
