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What is a Database?

What is a Database?

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Forward-thinking enterprises utilize databases to their advantage by thinking beyond the basic data storage and transaction needs and analyzing their data from multiple systems.

Learn how to become a Database Administrator:

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What is data?

Data is nothing but information that is collected in various formats such as numbers, text, media, and others. In the context of computing, data can be converted into a binary digital form that enables flexibility to be moved around and processed efficiently. For example, Intellipaat can have data such as the name, age, and educational qualification of its students, details of the various courses it offers, etc.

The term data is used as plural or singular. We come across the term raw data. It is data in its basic digital format. In its early days, when the importance of data started gaining momentum, terms such as ‘electronic data processing’ or ‘data processing’ were widely used in the IT industry.

As data grew exponentially over the years, the units of data measurement continued to grow. On the other hand, IDC predicted it would grow to 175 ZB by 2025. Databases, database management systems (DBMS), and relational database management systems (RDBMS) quickly arose to organize all these data.

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Database Definition

A database is a systematic or organized collection of related information that is stored in such a way that it can be easily accessed, retrieved, managed, and updated. It is where all data is stored, very much like a library that houses a wide range of books from different genres. Think of data as books.

In a database, you can organize the data in rows and columns in the form of a table. Indexing the data makes it easy to find and retrieve it again as and when required. Many websites on the World Wide Web are managed with the help of databases. To create a database so that the data is accessible to users through only one set of software programs, database handlers are used.

MySQL, SQL Server, MongoDB, Oracle Database,  PostgreSQL, Informix, Sybase, and others are all different types of databases commonly used today. These modern databases are managed by a Database Management System (DBMS). To interact with and manipulate the data stored in these databases, a widely used language called Structured Query Language (SQL) is utilized.

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Evolution of database

The database started with a file-based system about 50 years ago. In due time, it has gone through generations of evolution.

  • Databases were first introduced in 1968 as flat-file-based databases.
  • Then the Hierarchical Database came into existence and lasted until 1980. IBM’s first database, IMS (Information Management System) was based on this.
  • Charles Bachman developed the first Network data model, called Integrated Data Store (IDS). It was introduced in the early 1960s and standardized in 1971.
  • In 1970, the Relational Database was introduced.
  • Today, it is the era of Relational Databases and Database Management.

Components of database

Hardware:

Physical electronic devices such as storage devices, I/O devices, and many more. It can act as an interface between computers and real-world systems.

Software:

Programs for managing and controlling the overall database. DBMS itself is software. The OS, the database application programs that allow data access in DBMS, the network software that shares data, etc. are all examples.

Data:

It is the information that is gathered, stored, accessed, and processed by a DBMS, e.g., actual data, operational data, and metadata.

Procedure:

It is the specific set of instructions and rules to use a database for designing and running the DBMS, as well as to instruct users on how to operate and manage it.

Database access language:

This helps export data to and access the same from the database. To enter new data or update or retrieve the data from the database, you can write commands in the database access language. DBMS then displays the results in a user-readable form.

Applications of Database

FieldApplication
RailwaysReservation information, tickets, train schedules, etc.
LibraryBook information, issue date, etc.
BankingClient information, account, activities, loans, etc.
EducationStudent information, courses, grades, etc.
Credit card exchangeCard information, charges, etc.
Social MediaUser data, demographics, preferences, etc.
BroadcastUser information, bills, etc.
AccountsAccount information, transactions, etc.
ECommerceInventory information, purchases, invoices, etc.
HR ManagementEmployee information, salary, paychecks, etc.
ManufacturingSupplier information, bills, inventory, etc.
AirlineFlight information, schedules, etc.

Types of Databases

Relational database:

It is the most efficient way to access structured information. The data is organized into a set of tables that has columns and rows.

Object-oriented database:

Here, the data is represented in the form of objects, as in object-oriented programming.

Distributed database:

It has two or more files located in different places. The database may be in the same physical location on multiple computers or scattered over different networks.

NoSQL database:

NoSQL is a nonrelational database that contains unstructured and semistructured data. It rose in popularity as web applications came to be commonly used and became more complex.

Graph database:

It stores data in the form of entities and the relationships between them.

Cloud database:

This database runs on a Cloud Computing platform, and access is provided ‘as a service.’

Centralization database:

CDB is located, stored, and maintained in a single centralized location, for example, a mainframe computer, desktop, or server CPU.

Operational database:

Also known as OLTP or online transactional processing database, it is designed to create or update big amounts of data and store transactions performed by multiple users in real-time.

Data warehouses:

It is a central repository for data. It holds current and historical data in a single location for analytical reporting throughout the enterprise.

Become a Database Architect

Database Architecture

Database architecture in businesses and organizations involves the application of programming languages to design software. It mainly involves the design, implementation, development, and maintenance of the computer programs that store and manage data for businesses.

The architecture determines the design of a DBMS. The architecture can be either single-tier or multi-tier like 1-tier architecture, 2-tier architecture, 3-tier architecture, n-tier architecture, etc.

Advantages of Databases

  • Minimum data redundancy
  • Improved data security
  • Increased consistency
  • Lower updating errors
  • Reduced costs of data entry, data storage, and data retrieval
  • Improved data access using host and query languages
  • Higher data integrity from application programs

Database Languages

A DBMS provides appropriate language to users to help query databases and updates. It essentially creates and maintains the database. Some examples of database languages are SQL, Oracle, dBase, MS Access, FoxPro etc. Database languages are commonly divided into Data Definition Language (DDL), Data Control Language (DCL), Data Manipulation Language (DML), and Transaction Control Language (TCL).

Data Definition Language (DDL): Helps define data and their relationship to the other data types and creates databases, files, tables, and data dictionaries within databases

Data Control Language (DCL): Controls access to data and the database

Data Manipulation Language (DML): Supports basic data manipulation operations like allowing users to insert, retrieve, update, and delete data from the database

Transaction Control Language (TCL): Manages changes in the database made by the DML statement

Examples of Database

Few examples of Database are:

Microsoft SQL Server

SQL Server, developed by Microsoft, is a Relational Database Management System. It is built on SQL, the standard query language for Database Management Systems.

Oracle Database

Developed by Oracle Corporation, Oracle Database is based on a multi-model DBMS. It is widely used when processing online transactions.

MySQL

Based on Structured Query Language (SQL), MySQL is a Relational Database Management System. It is used in e-commerce platforms, data warehousing, etc. It is widely used as a web Database Management System.

IBM Db2

Db2 is a Relational Database Management System developed by IBM. It is designed to analyze, store and retrieve data efficiently.

PostgreSQL

An open-source Relational Database Management System, PostgreSQL is free to use. It is widely used for data warehousing.

Database Management System

Database Management System or DBMS is a type of software that helps manage a database. It is used to find and store information within a database. It can be modified according to the user’s needs. It adds a layer of security to the database.

Advantages of the Database Management System

  • The data is stored in a neater way and hence, more data can be stored.
  • A DBMS is a highly secure platform so confidential and high-risk data can also be stored and accessed, securely.
  • DBMS makes handling of data very simple.
  • Data inconsistency is greatly reduced by a well-designed DBMS.
  • Data can be accessed quickly.

Disadvantages of the Database Management System

  • Maintaining the software and hardware required for a DBMS is usually expensive.
  • The more data is fed into the DBMS, the more disk space it occupies.
  • Using DBMS could seem very difficult for someone from a non-technical background.
  • Since all the data is stored in one DBMS, if the software fails, all the data of the organization could be lost.

Conclusion

With the help of databases and other BI tools and computing tools, professionals in organizations are able to make use of the organized data to facilitate improved and effective decision-making, agility, and scalability. The different types of databases, along with the changes in the approaches of technology, advancements in automation, and the cloud are driving databases in new directions.

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About the Author

Data Engineer

As a skilled Data Engineer, Sahil excels in SQL, NoSQL databases, Business Intelligence, and database management. He has contributed immensely to projects at companies like Bajaj and Tata. With a strong expertise in data engineering, he has architected numerous solutions for data pipelines, analytics, and software integration, driving insights and innovation.