Relational Database Management System

In this tutorial, we will discuss Relational Database Management Systems.

Let’s first discuss What do databases do?

Databases have the ability to store large amounts of data. So when we search for any information on the internet then it finds all the URLs that meet the criteria. So far if you have been looking for a particular data or subject and type that in a web browser and click search then that’s actually talking to a database.

When you use Twitter, all messages are stored and indexed by #tags and every time any tweet is sent it is stored in a database that allows them to search them for information, with particular information, with particular #tags.

We use PhotoBucket for uploading images on the internet and they have been linked to the user accounts. Other people can access those images as well and also other programs like Facebook, Messenger, etc. Also, a lot of Google products are products of the database.

Databases are required to store large amounts of information quickly. So only information that has been streaming across the internet, there are databases out there. These databases are collecting that information.

Let’s see what information they are collecting?

Well, they are actually collecting data. Data is the most important part of the database. The function of a database is to store data to allow efficient and effective retrieval of information. So the data is an individual piece of data information that is storing and trying to index, for future retrieval down the track. So this allows us to find the data like which students are there in 12th this year? or what is the percentage of each student in a particular class?

So when we look at the following data information:

Data

• 01232020
• 12233450
• 29384355

Above we can see a list of numbers. Thus this list of numbers is actually just stripped data but when we apply some meaning to it for ex: Account number of any client then it becomes important information. That means this list of numbers is for a particular client or a file number in a warehouse where we can retrieve documents from a warehouse.

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Thus this list of numbers has gone from data to information. This is because we have actually given meaning to the data. Once we give data meaning, it becomes information which in turn becomes useful.

Therefore collecting a whole lot of piece of data and allowing for search at a later stage allows that data to become information. So when we are looking for a particular topic or data such as Restaurants, we can type that into Google and then it would search for all the sites that have restaurants and then displays the results as quickly as possible under a second.

We need to normalize the data. So the following data contains multiple categories:-

123, Auckland, New Zealand, 7556

Now, here is a complex piece of data. When we start looking at data we can actually see it is needed to break down into fields or categories, to help the database store this. Because when they are complex strings it requires a lot of processing parts for the computer to sort that information out and about breaking it down into fields which allows for quick retrieval.

So let’s see how do we break this data into fields and categories:

First of all, it is required to identify all the little pieces of information that bring this one complex piece of data. Once we are done with that we can categories this and break it into individual parts such as :

House Number: 123

City: Auckland

Country: New Zealand

Postcode: 7556

This allows the database to easily search for particular information, such as House Number or particular Postcode. We can just type in the number and the database will look in Postcodes to retrieve that piece of information rather than a complex piece of data. So normalizing data is very important for the efficiency of the database.

Now that we know how the data is normalized and structured within the database,

We need to understand how a database works:

Generally, it looks much the same as a Spreadsheet. We get an individual cell where rows and columns meet, we will actually get a piece of information or a piece of data. So we get Sara in the following database:  

Thus columns or fields allow us to categorize data into particular types. The rows that go across are called Records and these shows information about one particular entity within that database or dataset. You can see that a record is about one person, it could be about a vehicle or student or anything. So records are broken down into fields and fields contain pieces of data for that particular record. Now records and fields are stored into a particular table or file. This is how a database stores information about one category like above where it stores information about Employees.

You could have another type of class so you can have tables for Students or Classes or Teachers etc. A Relational Database management system helps to bring all those together.

Remember that Table should be for one particular entity i.e. for one particular entity or for a particular subject. So when we have multiple tables they help us in creating Relational Database Systems. The tables can be linked together and share all the information. So when we are looking to producing students timetables we can create Students, To find out which subjects, what teachers they have, etc. So the role of the database is to effectively organize the data for quick and speedy data retrieval.

We need to normalize the data to ensure that it is stored efficiently as it improves the user’s experience at the end.