Understanding The Difference Between Data Architecture & Data Modeling

The job of data architects and data modellers are often confused. Both of them deal with huge data but there is a subtle set of differences between the two roles.

Data Architecture Vs data Model

Data Architecture:

Data Architecture is a framework built to transfer data from one location to another, efficiently. It is full of models and rules that govern what data is to be collected. It also controls how the collected data should be stored, arranged, integrated and put to use in data systems of an organisation. In short, data architecture sets standards for all the data systems as a vision or a model of the functioning of the data systems interactions.

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Data Model

Data model could mean relationships between objects in a particular application or it could mean a set of concepts used in defining such relationships or formalisations. The job of a data model is to organise data elements in such a way that they are able to establish the relationship between these elements of data and how they relate to the real-world elements.

Data modelling is based on data and its relationship, and a model provides information to be stored and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software decision. A data model explicitly determines the structure of data and is often graphical in form. It can sometimes be referred to as a data structure, especially in the context of programming languages, and are complemented by function models, especially in the context of enterprise models. A data model is the set of definitions of the data to move through that architecture.

Data Architect Vs Data Modeller

Data Architect:

The job of data architects is to look at the organisation requirements and improve the already existing data architecture. One of the very important things in any organisations is keeping their data safe. Data architects keep this information safe and include security measures. They design and construct databases for organisations. They are responsible for setting the organisation standards for collection and interpretation of the data.

Their job is also to design the database structure, including how the data will move between departments. They are also given the power to decide what person outside of the organisation and also inside an organisation is allowed to access to data and they are also allowed to know the purpose of accessing the data. They develop a system to enable growth as the company grows and a system for a data backup in case of system failure. They also have to manage to keep the data interface the same across all applications.

Data Modelling:

The job of data modellers is to figure out the basic units of data. They create conceptual and logical models of the available data, to determine standard labels and notations to use across the organisation’s departments as the data is collected. Their main responsibility is to understand things like what data is useful for the client and other data requirements of a client. They investigate where the attributes of the data elements came from and define them appropriately. They also have to find relationships between data elements to help clients make sense of the available data and for that, they search for patterns with the conceptual data models. They also have to keep themselves updated with the new trends and standards within data modelling and also to make sure that the data is not repeated unnecessarily, helping in not adding complications in the data interpretation.

In Conclusion

Both roles of a data architect and data modeller overlap in an organisation. Both have more or less the same skill set but their responsibilities may vary a little. It is important to recognise the difference between the data architecture and data modelling.

Disha Misal
Found a way to Data Science and AI though her fascination for Technology. Likes to read, watch football and has an enourmous amount affection for Astrophysics.

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