Getting to the bottom of what structuring your data responsibly really means
Imagine constructing a skyscraper without a blueprint, figuring out how to lay concrete, align support beams and wire electrical in an ad-hoc way as the building takes shape.
Well, this is exactly what’s happening in data organisations today…
Data modelling, the foundational blueprint of the data ecosystem, is being neglected in the rush to adopt the latest technologies and deliver quick results. And we see a predictable mess of problems being addressed with short-term engineering fixes.
According to Joe Reis (who is writing a book on this topic now) a data model is:
A structured representation that organizes and standardizes data to enable and guide human and machine behaviour, inform decision-making, and facilitate actions
Data modelling has been a cornerstone of data management for decades, essential for companies to structure and understand their data. However, in recent years, the practice has become less popular, overshadowed by new data tools and technologies. This shift reflects a short-term perspective in the data industry, where immediate results are often prioritized over foundational principles.
The core issue is that data modelling requires a deep understanding of the concepts…