You’re finally ready to get down to real data modeling. We’ll start off with entities and their attributes. Entities are the basic building block of every data model. In this post, you’ll find out what they are and how to identify them.

What Is an Entity? What is a Specific Instance of an Entity?

Data models help us to identify what kind of information we’ll store in our system. We use such models to address the question What will the data in our system be about?

Entities are the things or objects in our system. They represent conceptual categories, not specific objects. For example:

In a store there may be a shop assistant called Eve. When she quits and another person called James is hired, he has the same role as Eve: he is a shop assistant. Moreover, the store can also hire other shop assistants. In our system, we will only have the general entity ShopAssistant . This entity is the role that both Eve and James have.

So, Eve and James are specific instances of the same general concept of a “Shop Assistant”. ShopAssistant is the entity in our system.

Let’s try another example. In a shop you have different products: a 9-carat white gold diamond ring, 7-carat yellow gold pearl earrings, and so on. The ring and the earrings are instances of the same concept – in this case, the Product. So our store system should have an entity known as Product .

Entities are like nouns. They can be almost anything, depending on the system. A car or a customer could be entities for an auto repair shop; student, teacher and class can be entities for a school data model. Patient, doctor, nurse, and room can be entities for a medical data model. As you can see, the list of entities is the vocabulary of a given system.

To sum up, we’ll say that entities can describe physical things, people, organization units, transactions, etc. In this series, you are going to see lots of different entities.

Naming Your Entities

Entities are represented with rectangles. Inside each rectangle, we put the name of the entity: Car , Person , Doctor , etc. Here are the entities from a car identification system:

The entity name should be singular ( Car not Cars ) and it shouldn’t be too long – we like to keep things short and simple. This is particularly important for huge data models with dozens of entities.

In this series of articles, entities are always going to be uppercase ( Student or Nurse instead of student or nurse ), but other data models may use a different system. Keep in mind, though, that short and descriptive entity names are always good form.

Filling Out the Details with Attributes

Each entity is associated with some details known as attributes. Remember shop assistants Eve and James? They have attributes: first and last names, a date of birth, eye color, and so on. Eve has two black cats and James loves playing computer games. Some of this data is important in our system (first and last names, birth date). Some of it is not relevant at all (we may love cats, but they have nothing to do with our system).

It’s not always obvious whether a certain piece of information should be stored in the system (e.g. James’ hobby might not be very important here, but it can prove useful in another system for a game development studio). It’s part of the data modeler’s work to make the decision about what is needed in the model.

We can say, then, that attributes are additional information about a specific instance of an entity. In this case, the entity is Shop Assistant, and the specific instances are Eve and James.

So what are Eve and James’ relevant attributes? Eve Larson was born on April 21, 1987. Therefore, we can say that the attribute for Eve’s first name is Eve . The value of the attribute last name for Eve is Larson . And Eve’s birth date (the value of the attribute date of birth ) is 21-04-1987 .

Likewise, James Green was born on June 6, 1990. So James’ first name is James , his last name is Green , his birth date is 9-06-1990 .

As with entities, each attribute has a name that tells us what information it contains. Attribute names are put inside the entity box.

When naming your attributes, avoid spaces. You can use camelCase to separate words in an attribute name. In this series, we’re going to keep all attribute names singular and camel case.

How Data Types Define Attributes

There are many types of information that can be stored in a specific attribute: text, numbers, dates, a logical value (i.e., true or false) and various others. Each attribute can only store one kind of information; this is its data type. Data types are a broad topic, and they’ll be getting an in-depth article later on. For now, let’s just have a quick look at data types.

For each attribute in an entity, you have to decide what kind of information (what data type) it will store. If, for example, you decide that the attribute district should contain the district number ( 7 ), you can’t fill the attribute with a text value later on ( Manhattan ). In our example model, a Person has a first name (text attribute), a last name (text attribute) and a date of birth (obviously, a date). A Car has a brand (text), a model name (text), a price (number) and a vehicle identification number (number).

Identifying Entities and Attributes

If you want to start data modeling successfully, you first need a description of your system. In a classroom situation, you will be given the description by your teacher or lecturer. In real life, it’s a bit more complicated – you need to start your work by talking to your customers, to the potential users of the system, and to domain experts. For instance, you could be given the following short description of your client’s blog:

We publish many posts. Each post has a specific author and each author has a nickname. After the post is written, we decide on the tags associated with the post. Finally, we have to choose a category for the post.

How do we find entities and attributes in a description like this? A common tip is to look for nouns. Each noun in the description may turn into an entity, an attribute, or an example in your data model. Examples are useful for finding relationships between entities; we'll cover them later in the series.

In our short blog description, we can identify the following nouns: post, author, nickname, tag, category. These nouns can become separate entities ( Post , Author , Tag , Category ) or attributes (nickname can become an attribute for Author ).

Don't worry if you have a hard time identifying entities and attributes – when building a data model, it’s common to go through multiple versions before you can achieve the desired model. Some nouns start as entities and end up as attributes or vice versa. Again, this is a very typical situation in data modeling. Just start by classifying some of the nouns and then, step by step, add a few more.

Find the Entities and Attributes in a Simple University System

Let’s use a basic education model to practice identifying entities and attributes. We’ll imagine that university authorities have asked us to prepare a simple system for class management. They gave us the following general description:

There are many students who take up various courses. All courses are run by lecturers. We have ID numbers for students, courses and lecturers. When a new student comes, we need to know their first name, last name and date of birth. When a new lecturer comes, we write down their first name, last name and their date of employment. All courses have names and descriptions so that students know what they cover. We also store the date when the course starts.

As you can see, we highlighted the most important nouns in the description. The first two sentences reveal the most significant nouns: students, courses and lecturers. They all describe people or units in our system, so they are perfect candidates for entities.

Now, let’s look for attributes. Students have their ID numbers, first and last names and dates of birth. Similarly, lecturers have their ID numbers, their first and last names, and their hiring date. Courses have an ID too, but they also have also names, descriptions and start dates.

Now that we have everything sorted out, we can present the description in a convenient, graphical form. As you remember, entities are represented as rectangles and attributes are listed inside them. Our final data model for a simple university system looks like this:

What’s Next?

In this article, we presented attributes and entities and we provided some examples to make you understand these concepts better. In the next article, you’re going to face a couple of exercises on finding entities. The exercises will help you get the hang of this essential step in data modeling.