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Definition of Logical Topology

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Why Do We Use Logical Topology?

It is the type of network topology which is used to define the architecture of network which is used for data transfer across network nodes. The network nodes include switches and nodes which can be used for creating the network. The logical topology helps to define the proper channel for data transfer and maintain the network. The logical topology is used to create a path to send signals across the network. It uses the network protocols which define the path for transferring packets. The most common example of network protocols is the ethernet protocol. The ethernet protocol defines the logical path for communication of different switches and nodes present in-network and sends packets across the network. It can be used to design the network structure. It can be considered as a blueprint of network and can help to implement the network physically in physical topology. The blueprint includes all the nodes and switches which will be involved in the network and how the data will flow in the network. It is used to define the high level of representation of a network.

Types of Logical Topology 1. Bus Topology

The bus topology is the type of logical topology in which all the nodes and switches are connected to only one single cable which can be also known as backbone or bus. The nodes are connected like half-duplex mode. In the bus topology, there is a host which is known as a station. The bus topology has multiple stations that have the capability to receive the network traffic and also have equal priority to transmit the network traffic in the network. And in the bus topology, the network is controlled by bus master which can be CSMA (carrier sense multiple access). In the bus topology, if any single segment goes down the whole network can be affected due to node failure.

The bus topology is easy to create and the devices can be connected to the bus easily.

The bus topology is very effective when the network size is small. The large network will contain a large number of nodes which can create a problem to maintain the network and can increase the chance of network failure. So the bus topology is effective for the small size of the network.

The network created by the bus topology is very reliable and the network can be easily maintained.

The setup cost for bus topology is very less as the length of the wire is small because all nodes are connected to the bus which decreases the network cost.

The other network device can be easily connected to the bus like connectors and repeater. The only requirement is joining cable which will join an external device to the bus.

The performance results of bus topology are least if it is compared to other network topologies.

As all the nodes are connected to one single cable and if that single cable goes down the whole network will go down. This creates a major risk of network failure in case of bus topology.

The packet collisions problem is there in bus topology. Due to packet collisions, the packet loss issue occurred which creates problems in data communication in a network.

2. Ring Topology Advantages of Ring Topology

The ring topology is effective for heavy traffic load compares to bus topology. The network congestion is not there in a ring topology.

Every node is responsible to transmit the data packets o adjacent nodes.

There is no central node in the ring topology which controls the network.

If any node goes down the whole network is failed in the ring topology because the connection is the break.

The new device cannot be added or removed from the network.

Importance

It helps to create the blueprint of the network. It helps to design the network and tells the structure of a network. Using the logical topology, the network can be implemented by using the physical topology. It helps to design the initial structure of the network and if any change is where it can be done before implementing the network physically.

Conclusion

It helps to design the network architecture. It includes information about nodes and switches which are placed in the network. There are majorly two types of logical topology which are bus topology and ring topology. It helps to identify the initial glitch in the network so that the network can be implemented without having any problems and data packets can be transmitted easily.

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## Know The Reason Why Do We Need C# Interface

Introduction to C# Interface

Interface, in C#, is a keyword, which holds a group of abstract methods and properties, which are to be implemented or used by an abstract or non-abstract class. Defining the methods are properties inside an interface which makes them public and abstract by default.

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In simplest terms, An Interface is like a Contract, where every member or component included in the body has to follow the contract, it defines what must be done. The interface does not contain any fields and is always defined by the use of the keyword “interface”.

Syntax:

Syntax starts with the interface keyword followed by the name for the interface and then the body.

{ }

As you can see, we have our standard syntax for Interface in C#, which begins with the ‘interface’ keyword then the name for interface and then abstract methods and properties inside the body. In C#, multiple interfaces can be implemented and used, inside a class or a struct. These interfaces can hold various methods, indexers, properties and also events as members.

Why do we need C# Interface?

Basically we have understood that there is no specific functionality inside an interface, if it is so, then why do we need Interface?

When to use Interface?

Security: When we have to simply hide some features and have to use those later. It is essential to hide a few details while only showing the details important to the user.

Multiple Inheritance: In c#, one class can inherit from a simple parent class, inheriting all its features. Multiple Inheritance is not supported in C# for the simple reason to not make C# complex. But with the use of an interface, multiple interfaces can be implemented into a single class.

Examples of C# Interface

Now that we have understood what interface is and its need. Let’s demonstrate a simple example of C# code with interface implementation.

Example #1

Program implements Interface and prints a simple statement.

Code:

using System; namespace MyApplication { interface SampleInterface { void InterfaceMethod(); } class Int_Example : SampleInterface { public void InterfaceMethod() { Console.WriteLine("nThis is simple example of Interface in C#."); } } class Program { static void Main(string[] args) { Int_Example myInterface = new Int_Example(); myInterface.InterfaceMethod(); Console.Read(); } } }

Code Interpretation: Starting with the use and namespace, a basic interface is generated as a SampleInterface that has a single method in its body. This method inside an interface does not have any particular body. Then we have our new class which is to implement the interface we created. Created with, class keyword followed by the class name and then implementing the interface with colon symbol followed by the interface name. Inside our class Int_Example, we have our earlier created interface method, which was bodiless by then, now we have added the simple print statement, which says, ” This is a simple example of Interface in C#.”

Then begins our mail class, namely Program, with the static void main statement. Inside our main class, we have created a new object for our Int_Example class which inherits interface. The new object is created and to the next line, our method created earlier is called up. Finally, our newly created object will call the earlier created method and the body inside that method will be executed here. With Console.Read(); the program will wait for user input before exiting.

Output:

Upon successful compilation and execution, the program must simply print the statement: “This is a simple example of Interface in C#.”

Example #2

Arithmetic operations using the interface.

Code:

using System; namespace arth_interface { public interface SampleInterface { void sam_add(int a, int b); void sam_sub(int a, int b); void display(); } class interface_class : SampleInterface { int x, y; public void sam_add(int a, int b) { int m, n; m = a; n = b; x = m + n; } public void sam_sub(int a, int b) { int m, n; m = a; n = b; y = a - b; } public void display() { Console.WriteLine("Added Value is:" + x); Console.WriteLine("Subtracted value is:" + y); } } class arth_interface { static void Main(string[] args) { interface_class obj_interface_class = new interface_class(); int fnumber, snumber; Console.WriteLine("Please Enter 1st Number to perform Addition and Subtraction:"); fnumber = Convert.ToInt16(Console.ReadLine()); Console.WriteLine("Now 2nd Number to perform Addition and Subtraction:"); snumber = Convert.ToInt16(Console.ReadLine()); obj_interface_class.sam_add(fnumber, snumber); obj_interface_class.sam_sub(fnumber, snumber); obj_interface_class.display(); Console.ReadKey(); } } }

We’ve declared two integers and then we have our first method to calculate addition. Here is the operation that needs to be done for addition and the same is for the subtraction. Then we have our display method, which consists of two print statements, printing addition and subtraction values of the numbers passed.

Finally, we have our class with the main method, where we initially created an object for our interface. Then the program prints “Please Enter the 1st Number to perform Addition and Subtraction:”, where the user inputs a first number and the later second number, for the purpose of calculations. With the object created earlier, the program calls the add and sub-methods from the interface and the same operations are done. At last, we have our display method, which displays our results as defined in the display method and ReadKey(); method holds up our program until any key is pressed.

Output:

The interface enables the plug-and-play method.

Complete Abstraction can be achieved by the implementation of Interface.

Along with making our code easy to maintain, concept loose coupling can be achieved.

Conclusion

We have understood what Interface in C# is. The proper syntax for an interface along with an explanation. To wrap it up, Interfaces in C# are a way to fill the emptiness of multiple inheritances in the language. Later we learned why do we actually need the interface in C# followed by the examples to demonstrate the understanding of the interfaces. The first example was to demonstrate simple use of interface while with the second example we implemented arithmetic operations, followed by Code Interpretation and output screenshot.

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## We Finally Know Why Sea Pickles Glow

David Gruber was on the southeast shores of Brazil when the ocean started glowing. He was testing out a squishy robotic hand that was attached to his submarine with the help of two colleagues when a colony of sea pickles swam by shining in their characteristic blue light. “They were fascinating,” says Gruber, a biology professor at Baruch College. The “alien-like creatures”, as he described them, created a long, tubular structure that moved through the water as a single organism.

Gruber and his team gently captured seven sea pickles using the soft robotic hand. Once back at the lab, they placed them in a darkened aquarium. To study them further, and to create the image above, they stimulated the animals—either by moving them or taking flash digital photographs—to make them glow and snapped the shots and videos with a Sony A7s II camera. Then, they got to work looking at the animals’ genetic code, trying to figure out which gene was responsible for their glow (They also studied animals collected in July of 2023 off Vancouver Island, in one of the biggest blooms ever recorded.)

The team published their findings earlier this week in the journal Scientific Reports, in what the researchers think is the first described instance of a bioluminescent gene in chordates, animals that have a cartilaginous skeletal rod supporting their bodies at some stage of their lives.

“This paper begins to uncover some of the mystery behind bioluminescence in chordates,” says biologist Rene Martin, a Ph.D. candidate at the University of Kansas who wasn’t involved in the study. Most of the things we know about bioluminescence in animals come from studying non-chordate creatures like jellyfishes or plankton. Chordates that can glow are hard to study. They are often hidden in the deep ocean and rarely come up to the surface. Whenever they do, they astonish those who get to see them. Sea pickles, for example, captivated a surgeon named Thomas Henry Huxley in 1851, who described the animals as “miniature pillars of fire gleaming out of the dark sea” while onboard the corvette HMS Rattlesnake.

Scientists have known that sea pickles have special cells called photosites, located as spots around their bodies, that allow them to glow. These cells contain genes called luciferases

that instruct the creatures to start a chemical reaction that stimulates a molecule called luciferin. This molecule releases light when the animal is disturbed.

Finding the bioluminescent gene is an arduous task, explains Gruber. After sequencing the animals’ DNA, they found several genes that looked like they could be a luciferase. They selected one of the most promising and created a synthetic replica. When they tested the gene, by making it interact with luciferin, the team got the spark they were looking for.

It is exciting that the researchers found a gene associated with bioluminescence, said the University of Kansas’ Martin in an email to Popular Science. Until now, the glow in other chordate animals had been explained by their diet or from a symbiotic relationship with glowing bacteria. This study found a gene similar to the one in animals like jellyfish, which could mean that animals using bioluminescence could have a common ancestor.

“For hundreds of years, humans have encountered these strange animals that can make their own light like a firefly. We know why and how some of them do it, but for some others it’s very hard to know,” Gruber says. “Over a hundred years, different scientists have studied this animal. It just feels cool to be part of this debate that has been ongoing for this long and to add another piece of information to it.”

## What Is Database And Why Do We Need It?

In today’s digital age, businesses rely heavily on efficiently organizing and retrieving vast amounts of data. At the heart of this data-driven world lies the database—an indispensable tool for storing, managing, and accessing information. But what exactly is a database? This comprehensive article delves into the intricate world of data bases, exploring their inner workings and unveiling their best features. We will uncover how databases empower businesses to streamline operations, enhance decision-making, and foster seamless collaboration with other entities.

This article was published as a part of the Data Science Blogathon.

What is Database?

A data base is a structured collection of data organized and stored systematically, typically in a digital format. It is a repository for storing and managing large amounts of information, such as text, numbers, images, and multimedia files. They provide a means to store, retrieve, update, and analyze data efficiently. They maintain data integrity, ensure consistency, and facilitate efficient data processing. A data base consists of tables composed of rows (records) and columns (fields) representing different entities and attributes. With the help of a data base management system (DBMS), users can interact with the data, perform queries, and manipulate information for various applications and business needs.

Also Read: Beginners Guide to Database

History of Data Base Management System Data Base Components

Database components work together to provide a robust and efficient data base system, allowing for effective storage, management, and retrieval of data for various applications and users. Here are some of the most common ones:

Tables

Tables are the fundamental building blocks of a data base. They represent the structured format for organizing and storing data. Tables consist of rows (records) and columns (fields) defining the data structure and attributes of the stored entities.

Schema

The schema defines the logical structure and organization of the data base. It specifies the tables, their relationships, and the constraints that govern the data. The schema acts as a blueprint for data storage and defines the data types, primary keys, foreign keys, and other constraints.

Queries

Queries retrieve, manipulate, and analyze data stored in the data base. They allow users to extract specific information based on criteria, perform calculations, and aggregate data.

Indexes

Indexes are data structures that improve the speed of data retrieval operations. They provide a quick reference to the location of data within a table, allowing for faster search and retrieval based on specific columns or keys.

Database Management System (DBMS)

The DBMS is the software that manages the database. It provides an interface for users to interact with the database, handles data storage, retrieval, and manipulation, enforces security and access controls, and ensures data integrity and consistency.

Data Manipulation Language (DML)

DML is a language that enables users to insert, update, delete, and modify data in the database. Common DML languages include SQL (Structured Query Language).

Data Definition Language (DDL)

DDL is a language used to define the structure and properties of the data base. It includes commands for creating tables, defining relationships, setting constraints, and managing the schema.

Data Backup and Recovery

Data base systems often provide mechanisms for backing up data and restoring it in case of data loss or system failures. Backup strategies include full backups, incremental backups, and point-in-time recovery options.

Security and Access Controls

Data base systems implement security measures to control access to data and ensure data privacy. User authentication, authorization, and encryption techniques are commonly employed to protect the integrity and confidentiality of the data.

Data Integrity and Constraints

Databases enforce data integrity by applying constraints such as primary keys, foreign keys, unique constraints, and check constraints. These constraints ensure the consistency and validity of data stored in the data base.

What is File System for Data Storage?

In File System, data is stored on a computer’s hard disk. The file system is a way of organizing files and directories on a computer. It is responsible for keeping track of where files are on the hard disk and how they are organized.

The file system is divided into the directory structure and the file data. The directory structure is a hierarchy of directories containing information about the files in each. The file data is the actual data that is stored in the files.

There are many different file systems, but they all essentially perform the same primary function: they allow you to store and organize your files. Some file systems are designed for specific operating systems, while others are cross-platform.

Difference Between Data Base & File System

There are many differences between databases and file systems. Still, the most fundamental difference is that databases are designed to store data in a structured way, while file systems are designed to store data in an unstructured way.

Databases are typically organized around data models, which define the structure of the data and the relationships between different pieces of data. This structure makes it easy to query the data and find the information you need.

On the other hand, file systems are designed to store data in a flat, unstructured way. It makes it difficult to query the data and find the needed information. Another difference between databases and file systems is that databases are typically designed to be accessed by multiple users simultaneously. In contrast, file systems are designed to be accessed by a single user simultaneously. Databases usually have locking and concurrency control to prevent data corruption, while file systems typically do not.

Source: Educba

Types of Databases 1. Relational Databases

Relational databases store data in tables. Tables are a type of data structure that store data in rows and columns. Rows represent records, and columns represent fields. It often store data that SQL can query. SQL is a language that is used to query data in relational databases. They are a powerful way to store data. They are easy to query, and we can use them to keep a large amount of data.

Where can we use Relational Databases?

Websites: SQL data bases can be used to store data for a website. This data can include user information, such as name and contact information, and website content, such as articles or blog posts.

Mobile apps: SQL data bases can power mobile apps. This data can include user information, such as name and contact information, and app content, such as articles or blog posts.

Businesses: SQL data bases can be used to run a business. This data can include customer information, such as name and contact information, as well as product information, such as inventory levels and pricing.

Limitations

SQL data bases are limited in their ability to scale horizontally. It means they cannot distribute data efficiently across multiple servers. It can be a problem when dealing with large amounts of data or when trying to provide high availability. Another limitation of SQL data bases is that they are not as flexible as NoSQL data bases regarding schema changes. Changing your data model without taking your data base offline can make it challenging.

Source: pragimtech

You have heard the term “Scaling database horizontally” in the above paragraph. It means distributing the load to multiple servers. Let’s dive deep into it and learn more about Database Scaling.

Database Scaling

Most people are familiar with the concept of scaling a database vertically. It means adding more resources to an existing data base server to increase performance, which might involve adding more RAM, a faster CPU, or storage.

Horizontal scaling is different. Rather than adding more resources to a single server, horizontal scaling involves adding more servers to a database cluster. We can do it by adding read-only replicas of the data base to different servers. Or, it can include sharding the data base, which means splitting the data into smaller pieces and storing it on other servers.

Which approach is best depends on the situation? Vertical scaling can be easier to implement and can be less expensive. But, it eventually reaches a point where adding more resources to a single server is no longer feasible. At that point, horizontal scaling becomes a necessary solution.

2. NoSQL Databases

NoSQL databases does not use the traditional table-based relational database model. Instead, NoSQL databases are designed to be scalable and flexible, and they use a variety of data models, including key-value stores, document, column-oriented and graph data bases.

Where can we use NoSQL Databases?

e ideal for storing large amounts of data. They are designed to scale horizontally, meaning they can easily add more nodes to the system as needed.

Handling high traffic: They are also suitable for handling high traffic. It is because they are designed to be highly available, meaning they can keep running even if one or more nodes go down.

Processing real-time data: They are also suitable for real-time processing data. It is because they are highly scalable, meaning they can easily add more nodes to the system as needed.

Limitations

NoSQL databases have many benefits, but they also have some limitations. One significant rule is that they are not well-suited for transactions that span multiple records. It do not support joins, which are necessary for transactions that update multiple records. Another limitation is that NoSQL data bases can be less consistent than traditional relational databases. It often do not enforce data integrity rules, such as foreign key constraints. Finally, it can be more difficult to query than relational databases. They often do not support standard query languages, such as SQL.

Source: educba

3. Graph Databases

A graph database is a database that represents and stores data using graph topologies with nodes, edges, and characteristics, enabling semantic searches. A crucial system idea is that the graph directly links data elements in the storage. We may immediately link data in the store together thanks to the relationships, and in many situations, we can access it with only one action. Although they have a distinct data model, graph databases are comparable to relational databases.

Where can we use Graph Databases?

There are a few different graph databases, and each has its use cases. Here are some examples of where you might use a graph database:

Social media networks use graph databases to map out relationships between users.

Fraud detection systems use graph databases to identify behavior patterns that may indicate fraudulent activity.

Recommendation engines use graph databases to find similar items and recommend them to users.

Networking and IT systems use graph databases to map out and visualize complex relationships between data.

Limitations

There are a few potential limitations of graph databases to be aware of:

They can be more complex to query than other databases. It is because you often have to traverse the graph to find the data you’re looking for, which can be time-consuming.

It can be more challenging to scale than other databases. Because each node in the graph is connected to other nodes, adding more nodes can quickly become complicated.

They can be less reliable than other types of databases. It is because the data in a graph database is often spread across many different nodes, making it challenging to keep track of everything.

Source: singhnaveen

Other Popular Databases 4. Object-Oriented Databases

These databases store objects, attributes, and methods, making them suitable for object-oriented programming. They enable complex data structures and support inheritance and encapsulation. Examples include db4o and Versant.

5. Hierarchical Databases

Hierarchical databases organize data in a tree-like structure, where each record has a parent-child relationship. They are suitable for storing data with one-to-many relationships. IBM’s Information Management System (IMS) is an example of a hierarchical database.

6. Network Databases

Network databases are similar to hierarchical databases but allow for more complex relationships, such as many-to-many. They use a network model to represent data and are useful for handling interconnected data. Integrated Data Store (IDS) is an example of a network database.

7. Columnar Databases 8. Spatial Databases

Spatial databases store and query spatial or geographical data, allowing for efficient storage and retrieval of location-based information. PostGIS and Oracle Spatial are examples of spatial databases.

Applications of Database

Databases find applications in a wide range of industries and domains where efficient data storage, management, and retrieval are crucial. Here are some common applications of databases:

Enterprise Systems

Databases are the backbone of enterprise systems such as customer relationship management (CRM), enterprise resource planning (ERP), and supply chain management (SCM) systems. They store and manage large volumes of data related to customers, sales, inventory, transactions, and more.

E-commerce

Databases power online shopping platforms, managing product catalogs, customer profiles, orders, payments, and inventory. They enable efficient search, personalized recommendations, and smooth transaction processing.

Financial Systems

Banks, financial institutions, and insurance companies rely on databases to store and manage customer accounts, transactions, loan information, claims data, and risk analysis.

Healthcare

Databases are integral to healthcare systems, maintaining patient records, medical histories, diagnostic reports, and treatment information. They support clinical decision-making, research, and data analysis for improved patient care.

Education Management

Educational institutions use databases to manage student information, course catalogs, schedules, grades, and academic records. They facilitate student enrollment, progress tracking, and administrative processes.

Human Resources

Databases store employee data, payroll information, performance records, and benefits details. They streamline HR processes, facilitate talent management, and support workforce analytics.

Social Media Logistics and Transportation

Databases are vital in logistics and transportation systems, managing inventory, tracking shipments, optimizing routes, and scheduling deliveries.

Research and Scientific Applications

Databases support scientific research by storing experimental data, genomic information, research publications, and collaboration records. They facilitate data sharing, analysis, and knowledge discovery.

Government and Public Sector

Databases assist government agencies in managing citizen information, public records, taxation data, land records, and administrative processes.

Examples of Databases

There are many examples of famous databases, but here are a few of the most popular:

DatabaseDescriptionOracleWidely used relational database management systemMySQLOpen-source relational database management systemMicrosoft SQL ServerRelational database management system by MicrosoftMongoDBNoSQL database for handling unstructured dataPostgreSQLOpen-source relational database management systemCassandraDistributed NoSQL database for scalabilityRedisIn-memory data structure store and cacheSQLiteLightweight, embedded relational database systemAmazon AuroraCloud-native relational database serviceNeo4jGraph database for managing interconnected data

1. MySQL

A free and open-source database management system is MySQL. Some of the biggest websites in the world, including Facebook, Twitter, and YouTube, use it as a standard option for online apps.

MySQL is a database management system developed in C and C++ on most operating systems. The most widely used database management system for PHP is MySQL.

A relational database management system is MySQL (RDBMS). Tables are used in relational databases to hold data. In a file system, tables function similarly to folders in that each table contains a collection of data.

We may utilize the robust MySQL database system for a variety of purposes. It has many functions and is simple to use.

2. PostgreSQL

With over 30 years of ongoing development, PostgreSQL is a powerful open-source object-relational database system built with a solid reputation for dependability, feature robustness, and speed.

PostgreSQL is an excellent choice for a database for several reasons:

It is free and open source.

It has a strong community of developers and users.

It is very stable and has a track record of handling high-traffic websites.

It supports a wide variety of data types, including geographic data.

3. Oracle Database

Oracle Database is a robust, reliable, and scalable relational database management system. It is the industry’s leading database, with over 400,000 customers worldwide. Oracle Database is used by some of the world’s largest organizations, including many Fortune 500 companies.

4. Cassandra Database

Cassandra is a NoSQL database that provides high availability and linear scalability. It is a distributed database designed to handle large amounts of data across many commodity servers while providing high availability with no single point of failure. Cassandra is an open-source project that is part of the Apache Foundation.

Cassandra features a ColumnFamily data model that allows for flexible data schema. Cassandra also has a built-in MapReduce framework that makes it easy to perform data analytics. Cassandra is written in Java and has been ported to other languages such as C++, Python, and Go.

Cassandra is used by some of the largest companies in the world, including Netflix, Facebook, and eBay. Cassandra has been proven to scale to handle massive data sets with very high availability.

Source: cassandra.apache.org

5. MongoDB

MongoDB is a powerful document-oriented database system. It has an index-based search feature that makes data retrieval quick and easy. MongoDB also offers a scalability feature, allowing it to handle extensive scale data.

6. Microsoft SQL Server

Microsoft created the relational database management system known as Microsoft SQL Server. It is a software product known as a database server. Its main job is to store and retrieve data when other software programs, which may operate on the same computer or a different machine over a network, require it (including the Internet). A part of the Microsoft Windows Server operating system is Microsoft SQL Server.

SQL Server 2024 introduces a new deployment option: Stretch Database. Stretch Database dynamically stretches your on-premises SQL Server databases to Azure. By dynamically extending the warm and cold transactional data in your databases to Azure, Stretch Database enables your applications to continue to access their data, even when it is moved to Azure.

SQL Server 2024 also introduces several other exciting new features:

Polybase enables you to query data stored in Hadoop clusters using the same Transact-SQL language used to query relational data in SQL Server.

Always Encrypted protects your most sensitive data, such as credit card and banking information.

Using Databases to Improve Business Performance and Decision-Making

Databases play a crucial role in improving business performance and decision-making by providing a reliable and organized repository of data. Here are some ways in which databases contribute to enhancing business outcomes:

Data Centralization

Data bases allow businesses to centralize their data, consolidating information from various sources into a single, unified location. This facilitates easy access, eliminates data silos, and promotes consistency and integrity.

Efficient Data Management

Data bases provide robust tools and functionalities for data management, including data storage, retrieval, update, and deletion. By organizing data in a structured manner, businesses can efficiently handle large volumes of information and ensure its accuracy and reliability.

Enhanced Data Analysis Business Intelligence and Reporting

Data bases integrate with business intelligence tools and reporting systems to generate meaningful insights and reports. By leveraging database-driven analytics, businesses can identify patterns, trends, and opportunities, enabling them to make informed strategic decisions.

Real-time Data Processing

Data bases equipped with transaction processing capabilities allow businesses to process and update data in real time. This is particularly valuable in scenarios where immediate data availability is critical, such as online transactions, inventory management, or customer support.

Improved Collaboration

Data bases enable multiple users or departments to access and share data securely. This fosters collaboration and enables cross-functional teams to work together, leveraging a unified source of information.

Streamlined Operations

By maintaining accurate and up-to-date data, data bases streamline business operations. From inventory to customer relationship management, databases ensure that relevant information is readily available, minimizing errors, redundancies, and inefficiencies.

Data Security and Compliance

Data bases provide mechanisms to enforce data security measures, including access controls, encryption, and auditing. They help businesses comply with data protection regulations and safeguard sensitive information.

Scalability and Performance

Data bases handle large volumes of data and support scalability. As businesses grow and data requirements increase, databases can accommodate expanding datasets and deliver optimal performance.

Integration with Applications

Data bases seamlessly integrate with various business applications, allowing for data exchange and synchronization. This integration enhances operational efficiency and ensures data consistency across systems.

Conclusion

In this article, we have talked about the various types of databases, their use, and also their limitations. Other than this, there are more types of databases, like Map-Reduce Databases or XML Databases; we will discuss them in upcoming articles.

We have seen above that no database is perfect. All of them have their benefits and limitations. An ideal database must be able to store data without any loss or corruption. It must be able to retrieve data perfectly and accurately. It must be able to update data ideally without any loss or corruption. Lastly, it must be able to delete data ideally without any loss or corruption.

Related

## The Science Of Attraction: Why Do We Fall For Certain People?

The Science of Attraction: Why Do We Fall for Certain People? We’re attracted to people who like the same things as us—politics, music, books. But why? And could it mean we’re judging those who aren’t like us too harshly?

A series of Boston University–led studies found people who believe they have a core essence that drives their likes and dislikes were more likely to be drawn to people with similar interests. Photo by The Gender Spectrum Collection

Relationships

The Science of Attraction: Why Do We Fall for Certain People? We’re attracted to people who like the same things as us—politics, music, books. But why? And could it mean we’re judging those who aren’t like us too harshly?

Sometimes life’s most meaningful relationships grow from the briefest of connections. Like when you go to a party and meet someone wearing your favorite band’s T-shirt, or who laughs at the same jokes as you, or who grabs that unpopular snack you alone (or so you thought) love. One small, shared interest sparks a conversation—that’s my favorite, too!—and blossoms into lasting affection.

This is called the similarity-attraction effect: we generally like people who are like us. Now, new findings from a Boston University researcher have uncovered one reason why.

Charles Chu says his research has plenty of uses in the business world, from managing staff to making deals. Photo by Dave Green

In a series of studies, Charles Chu, a BU Questrom School of Business assistant professor of management and organizations, tested the conditions that shape whether we feel attracted to—or turned off by—each other. He found one crucial factor was what psychologists call self-essentialist reasoning, where people imagine they have some deep inner core or essence that shapes who they are. Chu discovered that when someone believes an essence drives their interests, likes, and dislikes, they assume it’s the same for others, too; if they find someone with one matching interest, they reason that person will share their broader worldview. The findings were published in the American Psychological Association’s Journal of Personality and Social Psychology.

“If we had to come up with an image of our sense of self, it would be this nugget, an almost magical core inside that emanates out and causes what we can see and observe about people and ourselves,” says Chu, who published the paper with Brian S. Lowery of Stanford Graduate School of Business. “We argue that believing people have an underlying essence allows us to assume or infer that when we see someone who shares a single characteristic, they must share my entire deeply rooted essence, as well.”

But Chu’s research suggests this rush to embrace an indefinable, fundamental similarity with someone because of one or two shared interests may be based on flawed thinking—and that it could restrict who we find a connection with. Working alongside the pull of the similarity-attraction effect is a countering push: we dislike those who we don’t think are like us, often because of one small thing—they like that politician, or band, or book, or TV show we loathe.

“We are all so complex,” says Chu. “But we only have full insight into our own thoughts and feelings, and the minds of others are often a mystery to us. What this work suggests is that we often fill in the blanks of others’ minds with our own sense of self and that can sometimes lead us into some unwarranted assumptions.”

Trying to Understand Other People

To examine why we’re attracted to some people and not to others, Chu set up four studies, each designed to tease out different aspects of how we make friends—or foes.

In the first study, participants were told about a fictional person, Jamie, who held either complementary or contradictory attitudes to them. After asking participants their views on one of five topics—abortion, capital punishment, gun ownership, animal testing, and physician-assisted suicide—Chu asked how they felt about Jamie, who either agreed or disagreed with them on the target issue. They were also quizzed about the roots of their identity to measure their affinity with self-essentialist reasoning.

Chu found the more a participant believed their view of the world was shaped by an essential core, the more they felt connected to the Jamie who shared their views on one issue.

In a second study, he looked at whether that effect persisted when the target topics were less substantive. Rather than digging into whether people agreed with Jamie on something as divisive as abortion, Chu asked participants to estimate the number of blue dots on a page, then categorized them—and the fictional Jamie—as over- or under-estimators. Even with this slim connection, the findings held: the more someone believed in an essential core, the closer they felt to Jamie as a fellow over- or under-estimator.

“I found that both with pretty meaningful dimensions of similarity as well as with arbitrary, minimal similarities, people who are higher in their belief that they have an essence are more likely to be attracted to these similar others as opposed to dissimilar others,” says Chu.

In two companion studies, Chu began disrupting this process of attraction, stripping out the influence of self-essentialist reasoning. In one experiment, he labeled attributes (such as liking a certain painting) as either essential or nonessential; in another, he told participants that using their essence to judge someone else could lead to an inaccurate assessment of others.

“It breaks this essentialist reasoning process, it cuts off people’s ability to assume that what they’re seeing is reflective of a deeper similarity,” says Chu. “One way I did that was to remind people that this dimension of similarity is actually not connected or related to your essence at all; the other way was by telling people that using their essence as a way to understand other people is not very effective.”

Negotiating Psychology—and Politics—at Work

Chu says there’s a key tension in his findings that shape their application in the real world. On the one hand, we’re all searching for our community—it’s fun to hang out with people who share our hobbies and interests, love the same music and books as us, don’t disagree with us on politics. “This type of thinking is a really useful, heuristic psychological strategy,” says Chu. “It allows people to see more of themselves in new people and strangers.” But it also excludes people, sets up divisions and boundaries—sometimes on the flimsiest of grounds.

“When you hear a single fact or opinion being expressed that you either agree or disagree with, it really warrants taking an additional breath and just slowing down,” he says. “Not necessarily taking that single piece of information and extrapolating on it, using this type of thinking to go to the very end, that this person is fundamentally good and like me or fundamentally bad and not like me.”

Chu, whose background mixes the study of organizational behavior and psychology, teaches classes on negotiation at Questrom and says his research has plenty of implications in the business world, particularly when it comes to making deals.

“I define negotiations as conversations, and agreements and disagreements, about how power and resources should be distributed between people,” he says. “What inferences do we make about the other people we’re having these conversations with? How do we experience and think about agreement versus disagreement? How do we interpret when someone gets more and someone else gets less? These are all really central questions to the process of negotiation.”

“There are ways for us to go through life and meet other people, and form impressions of other people, without constantly referencing ourselves,” he says. “If we’re constantly going around trying to figure out, who’s like me, who’s not like me?, that’s not always the most productive way of trying to form impressions of other people. People are a lot more complex than we give them credit for.”

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## Why Do Skyscrapers Melt Things?

Talk about a hazardous parking job. Last Thursday, Martin Lindsay parked his Jaguar XJ across the street from the curvy 37 story, glass-and-steel skyscraper at 20 Fenchurch Street in London, and walked away. When he came back, his car had melted under the brunt of the sunlight reflecting off the still-under-construction building designed by Uruguayan architect Rafael Viñoly.

Parked in the “hot spot” where concentrated light bouncing off the curve of the building shines, the Jaguar’s paneling and side mirror melted. The developers of the building, nicknamed the “Walkie Talkie” for its distinctive shape, agreed to pay for the damages, which amounted to £946, more than \$1,400.

How the heck does a building melt a car?

“Fundamentally it’s reflection,” Chris Shepherd of the Institute of Physics told the BBC. “If a building creates enough of a curve with a series of flat windows, which act like mirrors, the reflections all converge at one point, focusing and concentrating the light.”

A concrete or brick surface diffuses light. Only 10 or 20 percent of the beam of light that hits the building gets reflected, and that light scatters in all directions. By contrast, a glass surface can reflect almost 100 percent of the sunlight that hits it, and can reflect that light back out in one direct beam.

“If you’re a car parked on the street, there are situations where you get both the direct sunlight you would always get [from the sky], plus the reflected light off the building,” John Frederick, a professor of atmospheric science at the University of Chicago, told chúng tôi “That must have been enough to put the temperature in that car over the top.”

Anyone familiar with solar power plants would have been able to tell the Walkie Talkie’s designers that they were going to be generating a lot of chúng tôi basically, the curves of the Walkie Talkie acted like a magnifying glass to concentrate the light on this one spot–right where Lindsay’s car was parked. (Some good pictures of the rays here.) According to Kheir Al-Kodmany, an associate professor at the University of Illinois at Chicago, anyone familiar with solar power plants would have been able to tell the Walkie Talkie’s designers that they were going to be generating a lot of heat with a southern-facing, concave facade. “The reflection of sun is getting concentrated to a single point because of the shape,” he says. “We use that exactly to generate power from solar energy.” Since it faces south, on a sunny day, it collects heat all morning and shoots it back at the street below. If it had been a northern-facing facade, it probably wouldn’t have been an issue.

Luckily, London isn’t a very sunny city, so this won’t be as much of a problem as it might be in a desert city like Abu Dhabi. The Walkie Talkie’s developers claim this phenomenon will only last for two to three weeks. “The phenomenon is caused by the current elevation of the sun in the sky,” they said in a statement.

Still, melting luxury cars is pretty bad press, so presumably they might want to take action before the problem resurfaces at this point next year. The AP reports the developers will be erecting a “temporary scaffold screen at street level” to minimize damage, but at some point, they’ll need a more permanent solution. To reduce the glare, Al-Kodmany says that there are coats and films that could still be applied to the glass, though the building might not look the same. “They can still probably retrofit the tower with some of these high tech films that would reduce the glare and reflection,” he says. “Of course, they need to consult the architect for aesthetics–it’s meant to be aesthetically unique.”

Has this been a problem before?

Yes, melted Jaguars are chúng tôi though melted Jaguars are unusual. Not long after Frank Gehry’s Walt Disney Concert Hall opened in Los Angeles in 2003, people began to complain that the sunlight reflecting off the building’s shiny exterior was making the condos across the street unbearably hot, as well as blinding drivers in nearby traffic. A study from the University of Southern California’s School of Architecture noted that on the sidewalk around the building, “freestanding lightweight objects get hot enough to soften plastic.” The offending panels of polished stainless steel were sanded down in 2005 to dull the glare.

In 2010, employees at the Vdara Hotel in Las Vegas dubbed the south-facing, curved tower the “death ray.” Sunlight reflecting off the hotel’s glass panes reportedly can melt disposable cups and singed the hair of at least one visitor. The building’s designer? Rafael Vinoly–the same architect responsible for London’s Walkie Talkie.

More recently, Museum Tower, a condo-filled skyscraper in the arts district of Dallas, has caused major headaches for the art museum across the street with its massive reflection. The Nasher Sculpture Center contends that intense sunlight reflected off Museum Tower is killing the plants in the museum’s sculpture garden and ruining exhibits. The museum removed a Picasso painting from display over concerns that direct sunlight would damage it, and at the request of the artist himself, closed down the James Turrell skyspace exhibit that had been designed with the site’s pre-condo natural light in mind.

Aren’t there some sort of regulations to keep a lid on this?

Not really, according to Duncan Phillips of RWDI, a Canadian engineering consulting firm that has been involved in coming up with solutions to Museum Tower’s reflection problem. “[T]here are no definitive standards,” he told me via email, though some places, like Singapore, have requirements for how reflective a building’s glazing, a shiny coating that can reduce the amount of heat a building absorbs from the sun, can be. But since those requirements usually only take into account the amount of reflection cast at at 90 degree angle from the glass, they don’t control for reflected light at other angles. “[T]he way you can experience this is to look at a plate of glass head on…and then slowly move to the side and eventually you will see a highly reflective surface,” according to Phillips.

Though the reflected light can create major pockets of heat, glassy skyscrapers are usually thought of as environmentally friendly, because reflecting the sunlight a brick surface would absorb keeps the building cool and air-conditioning costs down. Look at the difference in this thermal image of the reflective Freedom Tower (center) versus the buildings around it:

Thermal Skyscrapers

“As we get more shiny, glassy metal buildings, reflected light will become a bigger deal,” Frederick says. “The high reflection is good if you’re inside trying to keep intense sunlight out, but if you’re outside, you’ll be the recipient of that reflected light.” He suspects that though shiny buildings could heat up other buildings and objects in their vicinity, the effect is probably pretty small in terms of creating an urban heat island effect, which is when urban buildings and hard surfaces like asphalt trap heat, making cities hotter than their surroundings.

But it’s hard to tell how much the light bouncing off one building affects another, since that’s not usually something we measure. “The effect of one building on another building in its vicinity is something that never seems to be discussed,” Frederick says.

So, can I still park my car under a glass building?

Does your parking space look like it’s basking in a weirdly bright, ethereal glow? Does the building have a very shiny concave part? If that’s the case, then no, you probably shouldn’t park your nice car (or anything with plastic parts) there, in the gleam of concentrated sunlight reflecting off it. Especially not if it seems unusually warm in that patch of sunlight, and especially not around noon, when the sun is at its strongest.

Even if you wanted to, the city of London has cordoned off three parking spaces around the Walkie Talkie’s death ray to prevent anyone else’s Jag from melting. Still, anyone dumb enough to park their bike on that stretch of sidewalk might be in for a melted seat.

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