What is DBMS?
Database Management System (DBMS) is a software used for the storage, access and manipulation of data. Along with this, DBMS helps in securing data and getting useful insights from it. Common DBMS software are MySQL, PostgreSQL, Microsoft Access, MariaDB, SQLite and Microsoft SQL Server.
Why Learn DBMS?
It is said that data is the oil of the 21st century. With data being of utmost importance, there is a need to understand the system that helps us store and manage data in a standardized structure.
If you know DBMS, that means you can:
- Solve real-world problems by connecting them to DBMS relations and entities.
- Help businesses organize their data more effectively.
- and do a lot more....
Applications of DBMS
DBMS is extensively used in real-time systems due to its adaptability to various use cases. Most popularly it is used in banking, education, transport, tourism, human resource management, manufacturing and e-commerce for storing data of items or users and analyzing insights from it.
Advantages of DBMS
- DBMS helps in standardizing processes, thus ensuring uniformity in data structures.
- DBMS optimizes the needs of applications and helps users to accordingly retrieve, access and alter data.
- In DBMS, you can provide access to different users based on their roles. DBMS also has a concept called views which enables different users to obtain a different view of the table with different features.
- DBMS uses normalization which is a process used for this purpose. It splits relations (tables) whose attributes cause redundancy.
- DBMS allows multi-user transaction processing which means that users can access data in parallel and manipulate it without causing concurrency issues.
- It provides backup and recovery features that help create an automatic backup of data in a timely manner. This helps in mitigating unexpected hardware and software failures.
- Due to the centralized nature of a DBMS, it can be easily maintained, thus saving time for development and maintenance.
- Queries in DBMS are easy to learn and the different software that are used for this purpose are very easy to use.
- This tutorial will be helpful to computer science and IT students who are curious about learning basic to advanced concepts of DBMS.
- It will also act as a handbook for graduates and professionals (application programmers, database administrators, software engineers, product managers and end-users) who would like to delve deep into the domain.
Although DBMS is easy to understand, it is recommended to have fundamental computer knowledge that includes concepts of computer architecture, storage and hardware. Knowledge of data structures and algorithms and programming will be an added benefit.
What will you Learn in This DBMS Tutorial?
- You will learn the definition, history, characteristics, applications, pros and cons of DBMS with practical examples that will help you retain the concepts seamlessly.
- Not only will you be able to acquire an in-depth understanding about concepts like ACID, recoverability, normalization, schedules, and constraints` but also get a concise view of all of it whenever required through our DBMS Glossary.
- At the end of this, you will be able to fluently use SQL queries in solving real-world problems of various complexities.
- You will also be able to differentiate between relational and non-relational DBMS and determine their usability based on the situations.
Career Opportunity of Learning DBMS
DBMS is a major skill for software engineers and considering the huge demand for understanding and analyzing data, DBMS is a sought-after skill. Here are the few most sought-after opportunities that you can explore with this skill:
- Data Architect: Designs and builds intricate data frameworks based on the product requirements.
- Data Engineer: Develops database solutions as designed by the data architect.
- Database Manager: Maintains the database, normalizing it and preparing it for expansion.
- Data Analyst: Evaluates company's data and taking decisions regarding improving market position.
- Data Scientist: Designs and constructs new processes that would improve data mining and data production.