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About this sample
About this sample
Words: 2773 |
Pages: 6|
14 min read
Published: Jun 6, 2019
Words: 2773|Pages: 6|14 min read
Published: Jun 6, 2019
When there are people, there are data, and when there are data, there is its storage. The data may have a variety of attributes, classification, so grouping the random data under one thread could be another major difficulty. A proper system of logically organizing the data is required so that whenever there is a need to look at that large piece, it should at least look simple and not complicated due to its length.
So, when it comes to storage, modern digital systems have come up with a variety of options to save large chunks of data. But processing the large chunk of data is also another task at hand. The traditional systems of penning it down cannot be possibly an option. It would take time, energy to a large extent. Plus, requiring any specific amount of data in any future process would again be a cumbersome process. Here is where a dedicated program linked to storing and processing a huge amount of data came into existence known as the Database management system.
It efficiently does all the work with data. For example, in functions of complex entities such as the banks, insurance firms, schools, colleges, hospitals, where data is massive while the storage and organization also matter. At any point in time any piece of information could be required. At such things, the receiver must not necessarily know all of the information required. In such cases also, a DMS program helps, as it lets one find the keyword related to the data required to be fetched from the depository.
It comes as a handy tool helping us to manage a big amount of data in a structured way and also helps in designing the way our organization must look.
DBMS does all the work with the help of various models on the basis of which data would be arranged and the way it appears to the end user. It defines the structure of the database system as for how the data will be arranged by the DBMS program. It also tells about the linking of data and its sub-parts and other concepts regarding the data’s management too. So, the entity-relationship model is one such model of managing the huge data effectively. And the diagrams which are used to define the data management system using this model are known as entity relationship diagram.
The evolution of this system has not much history to it. It is simple and straight. According to some reports, it was designed by database designer Peter Chan and was published in the 1976 paper. After that, as per the needs, many forms and systems evolve for using these diagrams. These refinements were done by Charles Bachman and James Martin.
It is used by software users for computing and processing the data for businesses. It is a graphical representation of entities and their relationships with each other. Before establishing more about these diagrams, we must know a bit about the entity. In a computerized world, there are these technical words used for the representation of any entity. This means that the entity is a jargon related to the software world. It basically means any object or person or thing or place or any such single thing around which the huge data revolves. It turns out to hold a central position in these diagrams.
Now that we know what an entity is, we must proceed to know about its relationship with other objects. So, any object or for that matter an entity has various attributes to it. These attributes are closely related to the entity. Sometimes, two or more attributes must be related to each other. So, all this forms a kind of web or chain. And an entity relationship diagram seeks to represent this interconnection in an organized, structured manner.
It makes the appearance and understanding easy to comprehend. It looks like a flowchart, describing the entities and their relationship. The only advantage with these is that you don’t have to search randomly for any data, as this is organized so logically that you could directly reach to the desired information.
So further, there are few more technical jargons which may be used here and there in the documents relating to the ER diagrams. We must know these to get to the point straight.
Firstly, an entity is an object or thing about whom the data has to revolve. Most importantly, it is a real-world object.
Now the entities could be similar or vary as per the requirement. So, when we group together similar entities into one, the group is known an entity set.
As said earlier, there could be many characteristics given to an entity, or it may possess a lot of them. So, such characteristics are known as attributes.
Next up is the interconnection that comes up with entities and their attributes. For example, for a school teacher, ‘subjects,’ ‘Classes,’ ‘register,’ ‘marks,’ ‘copies,’ ‘examination’ could be the attributes. And some of them may be linked to each other. This forms the relationship that how the entities and their attributes are related to each other.
Then if we group together multiple relationships of the same type, it becomes a relationship set.
Finally, the logical, structured pictorial representation of all the terms mentioned above forms the entity relationship diagram. It is a sequential, ordered formation of the database.
How do we make diagrams?
Now that we know a great deal of information about the entity and various key terms, we must move on to the information regarding how do we make it. For making diagrams, there are standard symbols used, and as we dig deep and move further, there are variations as per the makers and their understanding. Coming to the standard and generally, the symbols which are used to represent various keywords are described as-
Entity: an entity is depicted by a plain rectangular box. In it, we could write the name of that entity.
Relationship: this is explained by a diamond box connecting two entities. Usually, these show a link between two entities, but in some cases, the entities could be linked to themselves also.
Attributes: now to move in a bit detail, these could be single valued, multi-valued, or be a derived one. Depending on what the attribute is, there are slight variations to the basic symbol. Generally, a single-valued or a basic attribute is shown by a simple oval. If there is a multi-valued attribute, then there would be two ovals-one over the other. And if the attribute is a derived one, there is this single oval made with dotted lines.
Connecting lines: these are simple solid lines which show a connection between the symbols used.
Well, this was all about the standard symbols. If we go more in detail, functions like ordinality and cardinality also arise these are represented by solid lines but with more wings on the side. That has further deviations, as per the Chen’s view, or as per the Martin’s view. It is used as per the requirement and understanding of the process.
With the evolution of any new technology, there has to be some strong reason behind its development. Have you ever wondered why they are the way they are?
Since the ER diagrams find immense use in businesses and their process, let us further discuss about their importance and uses. Firstly, it makes our complex data way organized. If anything is structured well, it gives the viewer and the reader a great deal of relief while going through it. It makes the comprehension of the process easier and makes it more prone to being remembered with a fair deal of accuracy.
Secondly, it helps visualization of the data and its comprehension in a way easier manner. And using our brain’s pictorial memory for memorizing could be a great tool. In terms of emergency presentations, it could save a lot of time on either side.
Thirdly, it interests the viewer even if he/she is not interested to go through a complex process and data. It is a general notion that if the visual appeal of any boring thing is good, we could give it a try once. So, it enhances the productivity at the workplace.
Fourthly, it helps in spotting errors in a fast-paced manner. Else trying to find as an error could be way time-consuming for complex databases. So, we could check for the desired attribute susceptible to an error. This saves time and energy for the redo required.
So, if any new technology or system could save businesses their time, energy and a lot of chaos, then it must be given a green signal.
We could consider an example to learn how to get these entity relationship diagrams going.
So, considering the same example of a school teacher, we have first to get all the attributes right and then set a diagram relating to his/her work. So, for a school teacher, there could be students, classes, subjects, no of lectures, and their relationship.
So, a diagram would look like-
The central rectangle would represent the teacher around whom the entities are related. All the ovals could represent the entities like classes, subjects, no of lectures, etc. the solid lines depict their relation with the common entity, i.e., the teacher. This could be more vivid as per the further needs, but a general diagram explaining the basic understanding would appear like this.
Even though entity relationship diagram is one model of representing the huge data of a database system, there are within it models catering to the specific data structuring techniques. There are these three entity relationship diagram models:
Conceptual data model: it is a basic ER diagram model. It tells about the data and its relationship in a generic way. It appears as if it is giving an overview of the process or the data concerned. It gives a rough idea of how the data is in relation to one another.
Logical data model: this is the next level from the conceptual one. It has more detail than the previous one. It gets us a deeper insight into any process. It gets us specific details of how the attributes are related. It forms the basis of getting to the next and higher level, i.e., the physical model.
Physical data model: it is the most complex model of the ER diagram. It is a kind of idea of physical manifestation of the previous model referring to the relational database. That is why a data scientist would need the logical model in front to develop and design the physical data model. Multiple physical data models could be made via a single logical data model.
So, in general, we could conclude that a data model used to make entity relationship diagrams varies in complexity from one level to other. The conceptual is the primary one which seems the easiest and simplest to view and understand. Next up comes the logical model, combining a few more steps from the previous one. Lastly, the physical model has all of it. It has all of the complex data structured into one. It is way too cumbersome.
As one goes above the hierarchy, one gets more detail, and the idea of the project one is working on. It helps as they are as per the varying needs of the business process.
For anything to be the best version of itself, it has to evolve from primary to secondary levels. So, by now, we know quite a detail on what these diagrams mean and a basic gesture of how these are made. To improvise and move further, let’s see how we can make our diagrams up-to-date and fresher and better. Here are some tips to build refined diagrams and the practices to follow.
The very basic thing to make these is to identify all the required entities for any project, in the first place. Missing out anyone would ruin the magic. So, keep them spaced a bit to look it more neatly and clear. Secondly, you could identify the relations between identities. This makes your job simple as you just have to get the related ones connected by solid lines.
Further, you could describe the relation using a diamond box and specify in it. Remember the relation you are specifying should be brief and apt. As this could determine one’s understanding of the process concerned. So, once you are done naming the relationship, it becomes easy to sort and spot for the exact one.
The next important consideration is like you shouldn’t have redundant relationships. Redundant here means that you should avoid having unnecessary relationships between entities. Those which are obvious and are understandable should be avoided to save space, time and energy. The same thing could be avoided with entities. One must not connect relationships with each other. This could be a blunder.
Lastly, you should draw the attributes regarding any entity. The same tip should make sense of this also. Redundant entities would ruin the sense again. Finally hit the last stroke by connecting entities and relationships with diagrams. This should complete your diagram and the representation.
Well for now know sufficiently high on the entity relationship diagrams. But to have something more, there are these types of relationships between entities. There are of four types. They are-
This is how entities are related and are defined so that it is hassle-free diagram making.
Help for you!
Well, imagine if all of this happens with the help of software. Yes, with the digital advancement, there are multiple software available to help you with this tiring process. Now you may think that why to learn about making these when there is software available for it. But then nobody could make things better than humans. So, the benefits that come up with using a software are-
So, find your business a good software that serves your needs and understands your requirements well. It will save time, energy and make way for improvising of your business process better.
Since ERD comes as a handy tool, almost all businesses would want to use this tool. The applications are so many that a school, college, hospitals, any entity using large chunks of data could use this. Moreover, with the advancement of technology, newer technology like the Big Data is emerging. Improved analyses of the data could be done with it. But anyway, the traditional ones never fade away.
So, this was all about entity relationship diagram. Next time you are with all the numbers and a plethora of information, you could think of using these simple systems to your rescue. With advancement, you also have built-in software to save yet again your time and energy. So, choose the one that could enhance your productivity at the workplace and make your data and its management better.
Hopefully, this could help you in some way. Although this topic forms a minuscule part of the big database management system, knowing these basic details could help you solve many of the complex problems ahead.
So happy data managing!
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