Information about data:

If you think about it, data is everywhere from the price of items at your local Store to the personal data collected from Government and schools. Our world is built on data, and SQL is a programming language that makes navigating this data much easier. Companies use databases mainly because spreadsheets and files aren’t scalable. While they may be suitable for small companies and start-ups that don’t collect large amounts of data, they can only store a limited amount of information. 

An Excel file, for instance, can only store approximately 1 million rows of data, and even this will slow down system performance considerably when users try to perform complex operations on it. In comparison, databases can load over 10 million rows of data in under a minute. furthermore, databases allow for easy data manipulation, analysis, and aggregation that simply cannot be done with a spreadsheet or text file. 

What is data, database and database management system



Besides exploring SQL and its uses, we’re going to look at how you can learn the language and the types of jobs you could get into if you pick up SQL. For instance, if you’re interested in working in the data industry, SQL is pretty essential learning.
There are many different types of databases used by organizations to store internal data, the most popular being relational databases.

Table of content:
  • What is Data?
  • What is Database?
  • different types of Database
  • What is Relational Database?
  • What is Database Management System (DBMS) ?
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What is database management system

What is Data?

 Data refers to the raw facts, statistics, or information that is stored in a database. It can be of various types, such as text, numbers, dates, images, or documents. Data represents the meaningful information that is processed, analysed, and used to derive insights.

What is Database?

Databases are vital for storing and managing large volumes of data efficiently. They provide a structured and organized approach to data storage, allowing for easy data access, manipulation, and retrieval. Databases are utilized in a wide range of applications, including business systems, e-commerce platforms, content management systems, scientific research, and more.

There are different types of Database:

  1. Relational Database
  2. Object-Oriented Database (OODB):
  3. Graph Database 
  4. Document Database  
  5. Key-Value Store
  6. Columnar Database 
  7. Time-Series Database
  8. Spatial Database
  9. In-Memory Database 
  10. NoSQL Database

These are just a few examples of the different types of databases available. Each type has its own strengths, use cases, and characteristics, catering to various data storage and management requirements.

What is Relational Database?

A relational database is a type of database that organizes data into tables consisting of rows and columns, with predefined relationships between the tables. It follows the relational model, which is based on the principles of relational algebra and set theory. The relational model provides a structured way to store, manage, and retrieve data, ensuring data integrity and facilitating efficient data manipulation.

In a relational database, data is structured into tables, also known as relations. Each table represents a specific entity or concept, and each row within the table represents an individual record or instance of that entity. The columns, also called attributes, define the different properties or characteristics of the entity.

The relationships between tables are established through keys, which are columns that uniquely identify each row within a table. The primary key is a special type of key that uniquely identifies each record in a table. Additionally, foreign keys are used to establish relationships between tables by referencing the primary key of another table.

The advantages of relational databases include:


Structure and Organization: Relational databases provide a structured approach to data storage, allowing for well-defined tables and relationships. This structure facilitates data organization and ensures data integrity.

  • Flexibility: 

 Relational databases offer flexibility in adding, modifying, and querying data. They allow for dynamic updates and provide the ability to perform complex queries, including joins and aggregations, to retrieve information from multiple tables.

  • Data Integrity:

 Relational databases enforce data integrity through constraints such as primary key and foreign key relationships. This ensures that the data is accurate, consistent, and reliable.

  • Scalability: 

Relational databases can handle large amounts of data and support the scaling of applications as data volume grows. They provide mechanisms for indexing, partitioning, and optimizing query performance.

  • Security: 

Relational databases offer robust security features, including access control, user authentication, and encryption, to protect sensitive data from unauthorized access.

  • Some popular relational database management systems (RDBMS) include:

  • MySQL: An open-source RDBMS widely used for web applications and small-to-medium-sized projects.
  • Oracle Database: A commercial RDBMS known for its scalability, security, and comprehensive feature set.
  • Microsoft SQL Server: A relational database system developed by Microsoft, commonly used in Windows-based environments.
  • PostgreSQL: An open-source RDBMS known for its extensibility, adherence to SQL standards, and advanced features.
  • SQLite: A lightweight, file-based RDBMS often used in embedded systems and mobile applications.

Relational databases have been the foundation of data management for decades and continue to be widely used in various industries for applications ranging from simple data storage to complex enterprise systems.

What is Database Management System (DBMS) ?


 A Database Management System (DBMS) is software that facilitates the management and organization of data in a structured manner. It provides an interface for users to interact with a database, allowing them to create, store, retrieve, and manipulate data.

The primary function of a DBMS is to enable efficient and secure storage and retrieval of large amounts of data. It acts as an intermediary between users and the database, handling tasks such as data organization, data manipulation, and data access. 

Here are some key aspects of a DBMS:

Data Definition: 

A DBMS allows users to define the structure of the database and its tables. Users can specify the tables, columns, and relationships between tables using a data definition language (DDL). This process involves defining the data types, constraints, and other properties of the data.

Data Manipulation: 

A DBMS provides tools and interfaces for users to insert, update, delete, and retrieve data from the database. Users can perform different types of  operations on the data using a data manipulation language (DML), such as SQL (Structured Query Language). DML allows users to write queries and commands to manipulate the data based on their requirements or use.

Data Security: 

DBMS systems offer security features to protect the database from unauthorized access, data breaches, and data loss. Access controls can be implemented to restrict user permissions and define user roles. Encryption techniques can be employed to secure sensitive data. Regular backup and recovery mechanisms can be set up to ensure data availability and integrity.

Data Integrity: 

Data integrity in DBMS (Database Management System) refers to the accuracy, consistency, and reliability of data stored in a database. It ensures that the data remains valid and reliable throughout its lifecycle, from the moment it is entered into the database until it is modified or deleted.

Think of data integrity as a set of rules and measures that help keep your data clean and trustworthy. Here are a few key aspects of data integrity.

Accuracy: 

Data should be correct and accurate. For example, if you have a field for a person's age, it should contain only numeric values representing their age, not random words or symbols.

Completeness: 

All required data should be present. If you have a form to collect information about a person, you would expect fields like name, email, and phone number to be filled out, not left empty.

Consistency: 

Data should be consistent across the database. If you have a field for gender with options "male" and "female," there shouldn't be other variations like "m" or "fem."

Uniqueness: 

Each piece of data should be unique. For example, if you have a field for "Employee ID," no two employees should have the same ID number.

Referential Integrity:

 This ensures that relationships between different tables are maintained correctly. For instance, if you have a "Customers" table and an "Orders" table, the "Customer ID" in the "Orders" table should correspond to an existing customer in the "Customers" table.

Protection against unauthorized changes: 

Data should be protected from unauthorized access or modifications. Only those with appropriate permissions should be able to alter the data.

In summary, data integrity in DBMS ensures that your data is accurate, complete, consistent, unique, and protected, making it reliable and trustworthy for making informed decisions and performing various operations in your application or business.

Data Concurrency: 

A DBMS manages concurrent access to the database by multiple users or applications. It ensures that multiple users can access and modify the data simultaneously without causing  any conflicts or inconsistencies. Concurrency control mechanisms, such as locking and transaction management, are implemented to handle concurrent operations and maintain data consistency.

Data Recovery: 

In the event of system failures, crashes, or data corruption, a DBMS provides mechanisms for data recovery and restoration. Backup and restore functionalities allow users to create copies of the database and restore them to a previous consistent state. Transaction logs and recovery algorithms ensure that data changes can be rolled back or replayed to recover from failures .

DBMS systems come in various types, such as relational DBMS (RDBMS), object-oriented DBMS (OODBMS), and NoSQL DBMS, each suited for different data models and requirements. They are widely used in applications ranging from small-scale personal databases to large-scale enterprise systems that handle large amounts of data.