Data modelling
Introduction to Data Modeling: What It Is and Why It Matters
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What is Data Modelling?
Data modelling is the process of analysing and defining all the different data your business collects and produces, as well as the relationships between those bits of data. Data modelling concepts create a visual representation of data as it's used at your business, and the process itself is an exercise in understanding and clarifying your data requirements.
Why data modelling is important
By modelling your data, you will document what data you have, how you use it, and what your requirements are surrounding usage, protection and governance.
Data modelling is important for various aspects:
Creates a structure for collaboration between your IT team and your business teams.
Exposes opportunities for improving business processes by defining data needs and uses.
Saves time and money on IT and processes investments through appropriate planning upfront.
Reduces errors (and error-prone redundant data entry), while improving data integrity.
Increases the speed and performance of data retrieval and analytics by planning for capacity and growth.
Sets and tracks target key performance indicators tailored to your business objectives.
Types of Data Modelling
There are three types of Data modelling.
Conceptual data modelling
A conceptual data model defines the overall structure of your business and data. It's used for organising business concepts, as defined by your business stakeholders and data architects. For instance, you may have customer, employee and product data, and each of those data buckets, known as entities, has relationships with other entities. Both the entities and the entity relationships are defined in your conceptual model.
Logical data modelling
A logical data model builds on the conceptual model with specific attributes of data within each entity and specific relationships between those attributes. For instance, Customer A buys Product B from Sales Associate C. This is your technical model of the rules and data structures as defined by data architects and business analysts. and it will help drive decisions about what physical model your data and business needs require.
Physical data modelling
A physical data model is your specific implementation of the logical data model, and it's created by database administrators and developers. It is developed for a specific database tool and data storage technology, and with data connectors to serve the data throughout your business systems to users as needed. This is the "thing" the other models have been leading to --the actual implementation of your data estate.