If you’ve ever worked with a data warehouse or business intelligence tool, then you’ve probably encountered a star schema. If you haven’t, then you might want to look into it… This elegant data modeling pattern has become the de-facto standard…
Data is not just the new oil; it’s the new language of decision-making. But before machine learning, embeddings, or even NoSQL, data had to be structured, described, and designed. Understanding how data models evolved, from Edgar Codd, Peter Chen and…
Now for something a bit different. In a world where data is no longer just rows in a database, the rise of vector databases and machine learning pipelines has pushed storage formats to evolve further. One of the most promising…
In modern organisations, data moves across teams, tools, and systems faster than ever before. With this speed comes a persistent risk: the moment a producer changes the shape, meaning, or frequency of data without warning, downstream consumers can experience silent…
In data management, semantic models address the challenge of understanding meaning and relationships within distributed data. They bridge business language and machine-readable data, enhancing interoperability, compliance, and self-service analytics. By defining concepts and semantics, they clarify terminology across systems, supporting AI integration and enabling better data governance and insights.
While the star schema dominates modern data warehousing, there’s another dimensional modeling pattern that occasionally enters the conversation: the snowflake schema. Named for its branching, crystalline structure when diagrammed, this approach takes a fundamentally different stance on one of data…
In data modeling, as in life, the answer to many questions is “it depends.” Should you denormalize your dimensions into simple star schemas or normalize them into snowflake schemas? The starflake schema says: why choose? Do both, where each makes…
For decades, the B-tree has been the backbone of database indexing, enabling efficient lookups, inserts, and range queries in block-oriented storage systems. For more information, please see my post on B-Trees: Its balanced structure and high fanout made it the…
I have previously had exposure to Domain Specific Language (DSL) using Xtext (). The DSL was used to define context and models. It meant we were able to give the business users and SMEs the tools they needed to build…
While dimensional modeling has dominated data warehousing for decades, another approach has been quietly gaining traction in enterprises dealing with complex, rapidly changing data landscapes. Data Vault 2.0 represents a fundamentally different philosophy about how to organize and manage enterprise…
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