Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow iconDBMS Tutorial For Beginners: Everything You Need To Know

DBMS Tutorial For Beginners: Everything You Need To Know

Last updated:
26th Jun, 2023
Read Time
8 Mins
share image icon
In this article
Chevron in toc
View All
DBMS Tutorial For Beginners: Everything You Need To Know

Before we begin exploring Database Management Systems (DBMS) in this DBMS tutorial, it is necessary to have a firm grasp of databases. 

Assume you work for a multinational firm with around a few thousand workers spread worldwide. Each employee will be assigned a unique employee ID, a job function, a manager, a ‘hire’ and ‘termination of agreement’ date, and a specific compensation amount. Since it isn’t feasible to create tables, categorise data, and write a thousand items on a piece of paper, databases were created in the 1960s.

Let us proceed with this DBMS tutorial so that you can grasp the basic concepts quickly.

What is a Database Management System(DBMS)?

Perhaps you have heard of MongoDB, Cassandra, OracleSQL, or MySQL. These are only a few of the many DBMS available. These programs enable you to save data, retrieve it, and conduct searches against databases.

A database is a digital representation of the ‘single long piece of paper’. It may be segmented, associated with another database, sorted according to various factors, and even compared to one another. 

Consider the following scenario: you want to analyse the salaries of individuals with the same job position and years of work experience. The only significant distinction is that they operate in different nations. You can accomplish this analysis using the DBMS or Database Management System. 

Explore our Popular Data Science Courses

Types of Database Management Systems

Database Management Systems can be classified into two types:

  • Relational Database Management Systems: A relational database is a data store that organises data into connected tables, as the name implies. Structured Query Language (SQL) lies at the heart of these systems since it is used to interface with and administer these databases, giving rise to their second moniker — SQL databases. 

In relational databases, data is stored in rows (records) and columns (attributes) that follow a specified model(a.k.a schema), ensuring that data is organised logically. Generally, there is one value for each property in each record, creating evident relationships between distinct data points.

  • Non-Relational Management Systems: A non-relational database is not tabular. It employs a variety of data models for saving, organizing, and obtaining information. They are referred to as NoSQL databases because they are not restricted to a table structure. 

They enable the storage of unstructured material such as texts, images, and various other file types. However, unlike in a relational database, data is not necessarily organised into rows and columns, as it would be in a flat-file system.

What are Keys in DBMS?

Keys are used to uniquely identify individual records or rows of data in the table. They also aid in the establishment and identification of links between table rows.

Different Types of Keys:

  • Primary Key: This key is used to identify a single instance of an object. Each schema has only one primary key. This key can be a value or a string that is not repeated more than once in the entire table. For example, an employee ID is the Primary Key for salary table or schema of employees. The employee ID is unique, and no two employees will have the same employee ID.
  • Foreign Key: Foreign keys are columns in a table used to refer to another table’s Primary key. A foreign key may also serve as the Primary key for another table.
  • Composite Key: When a Primary key has many attributes(more than one), it is referred to as a Composite key.
  • Candidate Key: Except the primary key, all other properties are considered candidate keys.
  • Super Key: A super key is a collection of attributes used to identify a tuple uniquely.

Check out our data science courses to upskill yourself.

Basic SQL commands for Managing Databases

SQL commands are a set of guidelines. It is used to exchange information with databases. Aside from that, it is also used to conduct certain activities, procedures, and data searches.

The most used SQL commands are explained below:

  • Data Definition Language(DDL): The DDL is used to create or edit database objects or the database’s structure, or to put it another way, to ‘define’ the objects or structure of the database.
  • CREATE: In the database, the command ‘CREATE’ creates new tables.
  • ALTER: The command ‘ALTER’ is used to add new columns or attributes to a table, or to modify the values of already-existing ones.
  • TRUNCATE: The command ‘TRUNCATE’ is used to remove all of the rows from a table and cleanse the available space in the particular schema you are working with.
  • DROP: The ’DROP’ command is used to remove or ‘DROP’ the structure and records that have been stored in the schema.
  • Data Manipulation Language(DML): The DML is used to modify databases per the user’s wishes by performing queries in the database. These are the most often used commands while dealing with databases. Data may be changed by adding or removing values from the database and altering values already present in the database.
    • INSERT: This command is used to enter or ‘INSERT’ data into a row of a table or schema.
    • UPDATE: This command is used to ‘UPDATE’ the column value of a table or schema.
    • DELETE: This command removes or ‘DELETE’ rows from a table. The DELETE command can be combined with the ‘WHERE’ command to delete more than one row.
  • Data Control Language(DCL): The DCL determines how users may access information stored in a database. For example, if a database has 50 users working on it, the Database Administrator may give or revoke access to certain areas of the database to the engineers.
    • GRANT: Access rights provide user access to a database using the ‘GRANT’ command.
    • REVOKE: It is basically the opposite of the ‘GRANT’ command. It removes a user’s permissions from one or more schemas or tables.
  • Transaction Control Language(TCL): The TCL is used to ensure that the database remains consistent and to handle the transactions that are initiated by commands of the Data Manipulation Language(DML).
    • COMMIT: This command is used to save the current state of a database after the required queries have been executed.
    • ROLLBACK: This command is used to return to the point of all unsaved changes in the schema.
    • SAVEPOINT: This command is used to roll back to a certain point in time without having to roll back the whole transaction in its entirety.

Top Data Science Skills to Learn

Top Careers to Pursue After Learning DBMS

Now you’ve taken the plunge and mugged up DBMS tutorial for beginners, it’s time to consider what careers can be pursued with this knowledge. Here are some of the top career paths for those who have a strong understanding of database management systems:

Database Administrator

A Database Administrator (DBA) is responsible for managing, maintaining, and troubleshooting databases in an organization. They store and organize data in order to ensure that it is accessible to users when needed. A DBA must also perform regular backups of the data in case of system failure or other issues. This role requires strong technical skills as well as a deep understanding of how databases work.

Data Analyst

Data Analysts use their knowledge of DBMS to collect, organize, and analyze data. They may use this data to find patterns or trends that can be used for decision-making within an organization. As a Data Analyst, you must be comfortable working with large datasets and using SQL queries to extract the information you need.

Database Developer

Database Developers are responsible for designing databases according to an organization’s business requirements. They create tables, store procedures, views, triggers, and other database objects in order to ensure that the data is properly stored and organized. Database Developers also write complex SQL scripts and queries in order to retrieve data when needed.

Business Intelligence Developer

Business Intelligence (BI) developers use their knowledge of DBMS to design and develop systems that allow organizations to collect, store, and analyze data. They create reports and dashboards using BI tools such as Tableau or Power BI in order to help management make informed decisions.

Data Scientist

Data Scientists use their knowledge of DBMS to gather, organize, cleanse, and analyze large datasets to discover hidden patterns and insights. This information is then used by businesses to improve their operations. To be successful in this role, you must have strong problem-solving skills as well as an understanding of various programming languages such as Python or R.

System Engineer

System Engineers are mostly responsible for planning, developing, and deploying databases within an organization. They also monitor the performance of existing databases and perform regular backups of data. To be successful in this role, you must have experience with database design and development as well as strong technical skills.

With a strong understanding of DBMS, there are many career paths to pursue. Depending on your interests and experience, you may pursue any of the above roles or even combine them for a more comprehensive job position. No matter which path you decide to take, good luck!

Curious about the foundational elements of database management? Learn about the types of keys in DBMS that play a crucial role in organizing, accessing, and maintaining data efficiently.


The need for highly skilled data-oriented employees is increasing with the proliferation of technological advancements in business. Because of the increased demand, the rivalry is becoming fiercer. Data scientists and analysts with a solid foundation in data science are in high demand by both large and small firms. They must stay updated with the data management systems on the market.

This database tutorial is just the beginning of your learning journey. With upGrad’s Master of Science in Data Science, you can deep dive into the world of data science. The course is offered in partnership with IIIT-B and Liverpool John Moore’s University, one of India’s leading research institutes. 

Students get the opportunity to connect with professionals in the field and gain knowledge and skills in cutting-edge technology and industry trends by participating in hands-on learning activities and sessions with their teachers.



Blog Author
Meet Sriram, an SEO executive and blog content marketing whiz. He has a knack for crafting compelling content that not only engages readers but also boosts website traffic and conversions. When he's not busy optimizing websites or brainstorming blog ideas, you can find him lost in fictional books that transport him to magical worlds full of dragons, wizards, and aliens.

Frequently Asked Questions (FAQs)

1What are the eligibility criteria for the Master of Data Science Program from upGrad?

A bachelor's degree with a minimum grade point average of at least 50 percent is required for admission. This course may be taken by anybody, regardless of their level of coding experience.

2What is DBMS?

A database management system (or DBMS) is a computerised data storage system.

3How many specialisations does upGrad’s Master of Data Science Program offer?

The program offers six specialisations in total.

Explore Free Courses

Suggested Blogs

42 Exciting Python Project Ideas & Topics for Beginners in 2024 With Source Code [Latest]
Summary: In this article, you will learn the 42 Exciting Python Project Ideas & Topics in 2024. Take a glimpse below. Mad Libs Generator Number
Read More

by Rohit Sharma

06 May 2024

Top 13 Highest Paying Data Science Jobs in India [A Complete Report]
In this article, you will learn about Top 13 Highest Paying Data Science Jobs in India. Take a glimpse below. Data Analyst Data Scientist Machine
Read More

by Rohit Sharma

12 Apr 2024

Most Common PySpark Interview Questions & Answers [For Freshers & Experienced]
Attending a PySpark interview and wondering what are all the questions and discussions you will go through? Before attending a PySpark interview, it’s
Read More

by Rohit Sharma

05 Mar 2024

Data Science for Beginners: A Comprehensive Guide
Data science is an important part of many industries today. Having worked as a data scientist for several years, I have witnessed the massive amounts
Read More

by Harish K

28 Feb 2024

6 Best Data Science Institutes in 2024 (Detailed Guide)
Data science training is one of the most hyped skills in today’s world. Based on my experience as a data scientist, it’s evident that we are in
Read More

by Harish K

28 Feb 2024

Data Science Course Fees: The Roadmap to Your Analytics Career
A data science course syllabus covers several basic and advanced concepts of statistics, data analytics, machine learning, and programming languages.
Read More

by Harish K

28 Feb 2024

Inheritance in Python | Python Inheritance [With Example]
Python is one of the most popular programming languages. Despite a transition full of ups and downs from the Python 2 version to Python 3, the Object-
Read More

by Rohan Vats

27 Feb 2024

Data Mining Architecture: Components, Types & Techniques
Introduction Data mining is the process in which information that was previously unknown, which could be potentially very useful, is extracted from a
Read More

by Rohit Sharma

27 Feb 2024

6 Phases of Data Analytics Lifecycle Every Data Analyst Should Know About
What is a Data Analytics Lifecycle? Data is crucial in today’s digital world. As it gets created, consumed, tested, processed, and reused, data goes
Read More

by Rohit Sharma

19 Feb 2024

Schedule 1:1 free counsellingTalk to Career Expert
footer sticky close icon