Industrial Applications of Database Management Systems
Database Management Systems (DBMS) are software applications designed to help users store, organize, and manage vast amounts of data efficiently. DBMS has numerous applications across various industries, from business operations to healthcare, finance, education, and government. By providing a reliable and efficient way to store and manage data, DBMS has become an essential tool for organizations and individuals alike. Here are some of the key applications of Database Management Systems:
1. ONLINE SHOPPING SYSTEM
Online Shopping apps have become an integral part of our life. A survey conducted found around 2.64 billion people are online buyers. This makes up 33.33% of the population with this growing trend, the number of online shopping apps has increased too.
Apart from the attractive user interface and various features that these apps provide, the main backbone for the apps is the database. Shopping apps generate huge databases. The attributes and entities for the database change according to each system’s requirement.
With a database of millions of users, several shopping items, and more than thousands of orders getting generated every day, the database management system plays a very crucial role in the functioning of such platforms.
· Role of DBMS in Online Shopping Systems
Here are some ways in which DBMS is used in online shopping:
Product catalogue management: Online shopping systems store and manage a vast amount of data related to products, including product descriptions, images, pricing, availability, and more. DBMS is used to efficiently manage this data and ensure that product information is up-to-date and accurate.
Customer data management: Online shopping systems collect and store customer data, including personal information, shipping and billing addresses, payment information, purchase history, and more. DBMS manages and secures this data, ensuring that it is accessible only to authorized personnel.
Order management: Online shopping platforms use DBMS to manage orders, including order processing, order fulfilment, shipping, and tracking, payment status, mode, etc. This helps ensure that orders are processed efficiently and accurately.
Apart from this, the data stored by DBMS is used to provide accurate personalized recommendations to users by using various machine learning algorithms.
· Database Management Systems used by Amazon
Product Catalogue Management: Amazon’s product catalogue is vast and complex, with millions of products spread across multiple categories. To manage this data, Amazon uses a combination of relational and non-relational DBMS. For example, Amazon Aurora is used for transactional data such as inventory management, order processing, and payment processing, while Amazon DynamoDB is used to manage unstructured data such as product descriptions, reviews, and ratings.
Customer Data Management: Amazon also uses DBMS to manage customer data, including account information, purchase history, and preferences. Amazon RDS is used to store customer data, and Amazon Redshift is used for data warehousing and analytics to gain insights into customer behaviour and improve the shopping experience.
Personalized Recommendations: Amazon uses machine learning algorithms to analyse customer data and provide personalized product recommendations. This involves collecting and processing large volumes of data, including customer behaviour data, purchase history, and product data. Amazon’s recommendation engine is built on a scalable infrastructure that uses DBMS such as Apache Cassandra to store and manage data.
Conclusion:
In conclusion, online shopping apps rely heavily on DBMS to manage their data infrastructure and provide a seamless shopping experience for their customers. The type of DBMS being used heavily depends on the type of data being stored.
2. SOCIAL MEDIA SITES
Social media sites have become an integral part of our lives, and they have transformed the way we communicate, interact, and share information. These sites generate massive amounts of data every second, and managing this data can be a daunting task. This is where Database Management Systems (DBMS) come in.
· How DBMS is used in Social Media sites:
User Data Management: Social media sites collect and store user data, such as profile information, friend lists, posts, comments, likes, and shares. DBMS helps manage and organize this data by creating tables, indexes, and relationships between different types of data.
Content Management: Social media sites host vast amounts of content, such as photos, videos, and articles. DBMS provides a way to store and manage this content, allowing users to easily access and share it.
Analytics and Reporting: Social media sites use DBMS to generate analytics and reports on user behaviour, engagement, and other metrics. This helps site owners make informed decisions about site design, content, and marketing strategies.
Personalization: DBMS is used to power personalization features on social media sites. For example, it helps recommend content, friends, and groups based on a user’s past behaviour and preferences.
Security: DBMS plays a critical role in securing user data on social media sites. It provides features such as encryption, access control, and backup and recovery mechanisms to ensure that user data is protected.
· Creating the perfect social media database:
Here are some steps you can take to create a social media database:
Define your goals: Before you start creating your social media database, you need to define your goals. What information do you want to collect? What do you want to do with that information? Defining your goals will help you create a database that meets your specific needs.
Determine your data sources: Social media data can come from a variety of sources, including public APIs, scraping tools, and third-party data providers. Determine which sources you will use to collect data for your database.
Choose a database management system: There are many database management systems available, each with its strengths and weaknesses. Choose a system that can handle the volume of data you plan to collect, provides robust search and filtering capabilities, and can scale as your needs grow.
Design your database schema: A well-designed database schema is critical for the success of your social media database. Define the tables, columns, and relationships that will store the data you collect. Use best practices for database design, such as normalization, to ensure that your data is structured correctly.
Implement data collection: Once you have designed your database schema, you can begin implementing data collection. Depending on your data sources, this may involve writing custom code, using third-party tools, or configuring APIs.
Monitor and maintain your database: As your social media database grows, it is important to monitor and maintain it. Regularly check for data quality issues, such as missing or inaccurate data, and resolve them as soon as possible. Monitor system performance and optimize your database as needed to ensure that it continues to meet your needs.
· Which Database is best for Social Networks?
Here are some of the popular databases used in social networks:
MySQL: MySQL is a widely-used open-source relational database management system. It is known for its high performance, scalability, and reliability. MySQL is used by many social media platforms such as Twitter, Facebook, and YouTube.
MongoDB: MongoDB is a NoSQL database that is designed to handle unstructured and semi-structured data. It is highly scalable and flexible, making it a popular choice for social networks that need to store and manage large volumes of data.
Cassandra: Cassandra is a highly-scalable NoSQL database that is designed to handle large amounts of structured and unstructured data. It is known for its ability to provide high availability and fault tolerance, making it a popular choice for social networks requiring high data consistency and availability.
Neo4j: Neo4j is a graph database that is designed to handle highly connected data. It is used by many social networks to manage relationships between users, content, and other entities.
PostgreSQL: PostgreSQL is an open-source relational database management system that is known for its robustness and extensibility. It is used by many social networks to store and manage complex data structures.
· The Different Databases Used by Social Media Platforms
Facebook uses a custom-built database called TAO (The Associations and Objects). TAO is a distributed graph database that is designed to handle relationships between objects, such as users, posts, and comments.
Twitter uses MySQL to store and manage its data. MySQL is a widely-used open-source relational database management system that is known for its performance and scalability.
LinkedIn uses a combination of MySQL and Apache Cassandra to manage its data. MySQL is used for storing user data, while Cassandra is used for storing other types of data, such as user activity and social graph data.
Instagram uses a combination of MySQL and MongoDB to store and manage its data. MySQL is used for storing user data, while MongoDB is used for storing other types of data, such as user-generated content.
Snapchat uses a combination of PostgreSQL and Apache Cassandra to manage its data. PostgreSQL is used for storing user data, while Cassandra is used for storing other types of data, such as messages and snaps.
Pinterest uses MySQL for its database needs. MySQL is used for storing user data, as well as pins, boards, and other metadata.
3. TELECOMMUNICATION INDUSTRY
DBMS is a field that is contributing to every sector of life and is now becoming an inherent part of every industry. It is used in various software applications, IOT applications, and many other applications. The telecommunication industry is one of the important parts of it. Storing various information of calls, user profiles, and history of various activities. Messages, calls, and various other mediums are available today. They have a great impact on our lives. They help in communication with other people and devices using various mediums. These help in the flow of information and helps in access to various information. The database is used in various fields nowadays and as humans are progressing, the use of database management systems has increased considerably. The database stores various information and that information is accessible to the user. It stores various information like call history, cloud services, real-time entries, user profiles, and many other things. This information can be accessed using various platforms like MySQL and various other services. These provide a platform for various operations on the data and for its retrieval.
· Various facilities provided by DBMS:
It becomes really hard to manage information from various user information, billing activities, call histories, and many other things. The information keeps on coming continuously and it becomes hard to manage it. DBMS provides a great platform for doing it. It can also generate invoices, process payments, and track account balances.
It also contributes to business insights. It keeps track of customer’s information, market trends, ups and downs in the trends, and management of network trafficking. The network needs to work smoothly and because various requests at the same time can lead to various problems and trafficking may lead to system failure and even crash. By efficiently managing the data, these problems can be neglected. Also, it gives protection to the personal details of the user. The user can decide to give access to anyone. Personal and banking details are stored in the database, but the companies give assurance that the data is safe. Because of this the ethics of privacy and important information can be protected from unauthorized hands. Mobile internet services, fiber optic services, call services, satellite services, and wi-fi services are some of the important services provided by telecom industries and all of them use data management as a core for various services. The management, access, and various processes are managed by the database. Messenger is a popular example of telecom; it uses radio waves for connecting devices.
· Some famous telecom companies:
1. Vodafone Group
2. NTT Docomo
3. SK Telecom
· Famous databases used by Telecom companies for providing services:
Oracle Communications Network Charging and Control (NCC) — This database is used by telecom companies to manage real-time charging and control of network services.
IBM InfoSphere BigInsights — A big data analytics platform used by telecom companies and is used to analyze vast amounts of data from various sources.
Teradata — This is a database management system used by telecom companies to store and analyze large amounts of data.
MongoDB — A NoSQL database used by telecom companies to store and manage unstructured data, such as social media data, log files, and sensor data.
Apache Hadoop — This is an open-source platform used by telecom companies for big data processing and analytics.
4. CREDIT CARD TRANSACTIONS
DBMS (Database Management System) plays a critical role in credit card transactions by efficiently storing, managing, and retrieving data related to transactions, customers, merchants, and financial institutions involved in the transaction process.
Some of the applications of DBMS in credit card transactions are:
Data Storage and Retrieval: A DBMS stores all the transaction-related data, including transaction amount, date, time, location, and merchant information. This data can be retrieved quickly and accurately by authorized personnel to investigate any fraudulent activity.
Fraud Detection: DBMS can be used to identify fraudulent transactions by analyzing transaction patterns and identifying anomalies. For example, a transaction that is much larger than usual for a particular customer may be flagged as suspicious.
Transaction Processing: DBMS can be used to process credit card transactions in real-time by verifying the cardholder’s identity, checking their account balance, and approving or declining the transaction.
Customer Management: DBMS can store customer information, including their personal information, transaction history, and credit limit. This information can be used to provide better customer service and personalized offers based on their transaction history.
Reporting: DBMS can generate reports that provide insights into transaction data, including transaction volumes, transaction trends, and average transaction amounts. These reports can be used to make business decisions and monitor the performance of the credit card processing system.
DBMS plays a crucial role in credit card transactions by providing a secure and efficient way to manage transaction data and prevent fraudulent activities.
· Applications:
American Express: American Express uses DBMS to manage its vast amount of transaction data, including customer and merchant information, transaction history, and financial statements.
Visa: Visa, one of the largest credit card companies globally, uses DBMS to manage its transaction processing system, which handles millions of transactions daily.
Mastercard: Mastercard uses DBMS to store and manage transaction data, including transaction history, customer information, and transaction volumes.
Discover Financial Services: Discover Financial Services, a direct banking and payment services company, uses DBMS to manage its payment processing system, which handles millions of transactions daily.
Capital One: Capital One, a leading financial institution, uses DBMS to store and manage customer data, transaction history, and financial statements related to its credit card business.
Overall, DBMS is essential for credit card companies to manage their transaction data, prevent fraudulent activities, and provide efficient customer service.
· Future technologies emerging in this field:
It is not possible to completely replace DBMS (Database Management System) with a new concept in credit card transactions as it is a critical component of the transaction processing system. However, there may be new technologies that supplement or complement DBMS in credit card transactions.
One emerging technology that could enhance the capabilities of DBMS in credit card transactions is blockchain. Blockchain technology provides a decentralized and transparent platform for recording and verifying transactions. It offers a secure and tamper-proof way to store transaction data, which could prevent fraudulent activities and provide greater transparency to customers, merchants, and financial institutions.
Another technology that could supplement DBMS in credit card transactions is machine learning. Machine learning algorithms can analyze large volumes of transaction data and identify patterns that could indicate fraudulent activity. This could improve fraud detection and prevention capabilities in the credit card processing system.
The conclusion is that, while there may be new technologies that supplement DBMS in credit card transactions, it is unlikely to be replaced entirely as it is an essential component of the transaction processing system. Instead, new technologies will likely complement DBMS and enhance its capabilities in managing transaction data, detecting and preventing fraudulent activities, and providing efficient customer service
5. PHARMACEUTICAL INDUSTRY
Database management systems (DBMS) are widely used in the pharmaceutical industry to manage and organize large amounts of data related to drug discovery, clinical trials, regulatory compliance, and marketing.
· Common applications of DBMS in pharmaceuticals:
Drug discovery: DBMS is used to manage chemical and biological data related to drug discovery, such as chemical structures, target proteins, pharmacological properties, and toxicity data. DBMS can help scientists to search and retrieve relevant data, analyse relationships between different data types, and build predictive models for drug development.
Clinical trials: DBMS are used to manage data related to clinical trials, such as patient demographics, medical histories, treatment protocols, adverse events, and efficacy outcomes. DBMS can help researchers to monitor and analyse trial data in real time, identify safety issues, and generate statistical reports for regulatory submissions.
Regulatory compliance: DBMS are used to manage data related to regulatory compliance, such as drug registration, labelling, manufacturing, and distribution. DBMS can help companies track and report compliance data to regulatory agencies, ensure data accuracy and consistency, and maintain audit trails for quality control purposes.
Manufacturing: DBMS are used to manage data related to drug manufacturing, such as raw material inventories, batch records, and quality control data. Companies use DBMS to track and optimize manufacturing processes, ensure product quality, and meet regulatory requirements.
Marketing: DBMS are used to manage data related to drug marketing, such as sales volumes, customer demographics, pricing, and promotional activities. DBMS can help companies to analyse market trends, segment customers, develop marketing strategies, and track the effectiveness of marketing campaigns.
Supply chain management: DBMSs are used to manage data related to the supply chain, such as inventory levels, shipping schedules, and supplier performance. Companies use DBMS to optimize the supply chain, reduce costs, and ensure product availability.
Overall Conclusion, DBMS plays a critical role in enabling the pharmaceutical industry to manage and analyse complex data related to drug discovery, clinical trials, regulatory compliance, and marketing, and to make informed decisions based on this data.
