Trending March 2024 # Trading Or Investing? What Is The Difference? – Dr. Yasam Ayavefe Explains # Suggested April 2024 # Top 7 Popular

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Active stock trading has always been a popular activity. However, during the COVID-19 pandemic, its popularity skyrocketed. Everyone is more interested in learning about the stock market and how to maintain financial stability these days. Nevertheless, it is critical to note that the terms “active” and “investor” hardly belong together. When it comes to entering the stock market, trading and investing are two quite distinct approaches. In essence, there are two types of stock market traders, and their behaviors can be summarised as follows: ➡Investing -those who use fundamental analysis to determine the long-term value of a company’s stock by analyzing its financial statements (long-term gains). ➡Trading – technical analysts and chart readers who believe that all fundamentals have already been taken into account in the price of an asset. (short-term gains)

Investing vs Trading

Investing and trading are two entirely distinct strategies for profiting in the financial markets. Although their approaches are diametrically opposed, investors and traders share a common objective: a profit over time. By purchasing and keeping securities, investors seek long-term returns on their investments. By contrast, traders seek to profit from the opportunities presented by both increasing and collapsing markets over a shorter time period. Generally, traders earn smaller but more frequent profits. Another critical distinction is the ownership of acquired securities, such as company stock. Investing in shares entails ownership of those shares, i.e. you own a portion of the corporation. By contrast, trading those identical equities on the stock exchange does not constitute ownership. You trade price differentials by forecasting a price increase or decrease.

Conclusion

Your financial ambitions, mental agility, and tolerance for market volatility all factor into whether trading or investing is a better fit for you. Individual stock bets rarely make sense for investors pursuing long-term goals such as retirement. This is not to say, however, that actively trading or developing a position in a certain company is a bad idea. Moderation, as with everything else in life, is necessary.  

Find out more about Dr. Ayavefe and his work here:

Active stock trading has always been a popular activity. However, during the COVID-19 pandemic, its popularity skyrocketed. Everyone is more interested in learning about the stock market and how to maintain financial stability these days. Nevertheless, it is critical to note that the terms “active” and “investor” hardly belong together. When it comes to entering the stock market, trading and investing are two quite distinct approaches. In essence, there are two types of stock market traders, and their behaviors can be summarised as follows: ➡Investing -those who use fundamental analysis to determine the long-term value of a company’s stock by analyzing its financial statements (long-term gains). ➡Trading – technical analysts and chart readers who believe that all fundamentals have already been taken into account in the price of an asset. (short-term gains)Investing and trading are two entirely distinct strategies for profiting in the financial markets. Although their approaches are diametrically opposed, investors and traders share a common objective: a profit over time. By purchasing and keeping securities, investors seek long-term returns on their investments. By contrast, traders seek to profit from the opportunities presented by both increasing and collapsing markets over a shorter time period. Generally, traders earn smaller but more frequent profits. Another critical distinction is the ownership of acquired securities, such as company stock. Investing in shares entails ownership of those shares, i.e. you own a portion of the corporation. By contrast, trading those identical equities on the stock exchange does not constitute ownership. You trade price differentials by forecasting a price increase or chúng tôi financial ambitions, mental agility, and tolerance for market volatility all factor into whether trading or investing is a better fit for you. Individual stock bets rarely make sense for investors pursuing long-term goals such as retirement. This is not to say, however, that actively trading or developing a position in a certain company is a bad idea. Moderation, as with everything else in life, is necessary.

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Hdg Explains: What Is Telnet?

When most people think of the internet, what they’re really thinking of is the Web. However the physical network that makes up the internet carries far more than just websites and the public-facing services we all use every day. 

In fact, most of the internet isn’t related to the web at all, but rather a whole slew of other internet services that use various “protocols”. HTTP or hypertext transfer protocol is used to serve websites to your browser, as one example. Telnet is also an internet protocol, but one with a different history and some interesting uses. 

Table of Contents

But what is telnet? In this article you’ll learn just that.

What Is Telnet?

Telnet is a text-based network protocol that lets a client (that’s you) communicate with a remote computer, somewhere out there on the internet. Usually, Telnet connections run over Port 23 and, just like websites, Telnet services have a specific address.

These days, just about everything from a smartwatch to a smart TV has full computing power, so dumb terminals don’t really get much use anymore. In order to use a Telnet service today, you’ll need an application known as a terminal emulator. The good news is that there are a whole bunch of great free terminal emulators out there for every operating system.

You might be thinking that Telnet doesn’t sound all that relevant anymore. While it is a more obscure internet service, there’s a sizable and dedicated Telnet community worldwide.

It also still has a very important role in low-bandwidth remote computer management. Which means that not only is Telnet far from dead, it still has a bright future ahead of it. Before we get to that, however, let’s take a quick look at where Telnet came from.

A Brief History Of Telnet

Before the internet of today, there was ARPANET. A military and academic computer network at a time when the only people who had computers worked for government agencies or institutions. The computers in question were massive machines that filled entire rooms. This was before the idea of a personal computer was on anyone’s mind.

Getting computers to talk to each other over this new network was no easy task. Mainly because these machines each had very different designs and architectures from one another.

What was needed is a single shared language. In 1971, the first proposal for the Telnet protocol was drafted. However, It would take more than a decade for Telnet itself to be released as a working technology. In 1983, the very first iteration of telnet protocol was released to the world.

Telnet As A Remote Management Tool

Telnet can be used to send commands to remote systems and therefore control them through the terminal interface. This is rarely done these days, with the SSH (Secure Shell) protocol mostly replacing the purpose and function of Telnet. 

However, Telnet is still important, because systems that run operating systems from previous eras, but are still in use today, might only be accessible through Telnet. Some internet appliances, such as certain routers, might also only respond to Telnet commands. 

What Is Telnet vs Secure Shell

Telnet was developed at a time when the idea of cyber security wasn’t really on anyone’s mind. Since only trusted actors had computers with network access, the idea that someone would hack into a computer was pretty far-fetched. 

Today billions of people have a computer as well as an internet connection. Hackers are constantly attacking remote systems, which means that they are always looking for a new vulnerability. Since Telnet sends its commands in plain text and everyone knows which network port it uses by default, it’s fairly trivial to intercept or modify the data.

Secure Shell solves this issue by using strong encryption on all the data it sends and receives. This is one of the main reasons it has supplanted Telnet. That being said, these days there are also ways of applying encryption to Telnet, though it’s not an integrated part of the protocol

How To Access A Telnet Service

To connect to a Telnet service, all you need is a terminal emulator and the address of the computer you want to connect to.

There are plenty of terminal emulators. Most of them are free. In this case we’re going to use the popular Tera Term. As a demonstration, we’ll connect to a Telnet service that uses ASCII text to retell the entire first Star Wars film.

Usually, with a traditional terminal application you’d type “telnet” followed by a space and the address of the service. You may also have to specify the port in the command, which is usually port 23 for Telnet. However, Tera Term has a graphical interface, so all we have to do is fill in the screen like so.

Awesome! Right? Let’s not stop the fun there. Here are some more Telnet services you can play around with while you have that terminal app out.

Cool Telnet Services

Now that we’ve covered the essential facts about Telnet, there’s no better way to round off this crash course than to point you in the direction of some interesting places you can visit right now. 

Telnet.org maintains a huge list of Telnet places to visit. You should head over there to get the more obscure destinations, but here are the highlights most people will get a kick out of:

What Is The Best Cryptocurrency Trading Platform?

The rising value and popularity of crypto have led to a sharp rise in the number of people who trade cryptocurrencies, even though fraud has been and will continue to be a problem. But today, the best apps, exchanges, and cryptocurrency investment platforms exist. In addition, it makes it easier to understand how it works.

There are many ways and places where you can invest in cryptocurrency. We have Bitcoin ATMs, wire transfer services, exchanges, trading platforms, and online brokers on our list. Traditional investors should know that cryptocurrency platforms may have very different pricing structures. Limited customer service options and put the onus of security on the investor.

Coinbase

When you’re starting, Coinbase is the best cryptocurrency exchange. It has a simple interface, many educational materials on blockchain and volatility, and strong security measures.

If you know about digital currencies, you don’t need to be told about Coinbase. The exchange is one of the biggest and most well-known in the US. Many saw its first public offering last year as a sign that the crypto market was on the right track.

The Coinbase platform does an excellent job of making it easier for people to invest in cryptocurrency. It has a simple way to get started that makes trading easier. The user interface of the platform also makes it easier to manage cryptocurrency.

Coinbase has a lot of easy-to-use and comprehensive learning tools. Through its Earn program, Coinbase encourages customers to use these tools. They teach them how to trade bitcoin in exchange for free digital currency.

The security features of the exchange are worth mentioning. Coinbase covers custodial accounts with a $250,000 insurance policy. It uses two-factor authentication on all platforms and keeps 98% of users’ bitcoin offline. So even though prices are rising, one reason to use Coinbase is its security measures.

If you like Coinbase but wish it had more complex trading and charting tools. Then, you should check out Coinbase Pro, the company’s second exchange platform.

Abra

Abra is a global cryptocurrency exchange that connects buyers and sellers from more than 150 countries. Abra stands out from other cryptocurrency exchanges. It is because it has a wide range of crypto products and services and doesn’t charge any fees to trade.

There are 80 different cryptocurrencies to trade, accounts that pay up to 10% interest on eligible assets, loans backed by bitcoin, over-the-counter (OTC) trading, and other courses for people who are starting. Its OTC services include savings accounts that pay interest, loans, and services tailored to institutional clients’ needs.

Binance

Binance.US was our top choice because it had the lowest fees compared to the other exchanges we looked at.

Binance is the most significant cryptocurrency exchange trading volume, and chúng tôi its US version, has many of the same benefits. One of its many good points is that its maker/taker fees are competitive (the most you could pay is 0.1% of the whole transaction). This fee is already meagre and will decrease even more if you trade more.

One of the most used utility tokens, Build & Build (BNB), can be used to get discounts when you buy or sell on Binance US.

US dollars can be used on the exchange to buy over 120 different cryptocurrencies. It saves customers the trouble and cost of changing currencies. Advanced users may like the platform’s detailed market dashboards, margin trading, many order types like limit orders, market commands, and stop limit orders, and a wide range of discounts and buy options.

Because chúng tôi has many protections against cryptocurrency fraud and cyberattacks, we were able to decide that it was the most secure cryptocurrency exchange.

It also has a money market, prepaid Visa cards that can be used to spend crypto, crypto loans, and DeFi, a wallet that doesn’t hold your crypto but lets you transfer it at your own pace and earn interest on tokens.

Kraken

Kraken works with more than a hundred different digital currencies, giving investors both large and small a wide range of options. Binance isn’t as well known around the world as Kraken. About 200 countries can now use the site to trade.

Kraken also lets you trade futures and use margin. With its margin accounts, you can borrow up to five times the amount you put into your bitcoin trading account. In addition, Bitcoin, Ether, Bitcoin Cash, Litecoin, and Ripple can all be traded on futures markets, where investors can buy and sell the underlying asset at a fixed price on a specific date.

Conclusion

Choosing the proper cryptocurrency exchange is very important if you want to start trading or investing in cryptocurrencies. There is a good option for anyone who wants to change a wide range of digital assets or have the best trading experience on a mobile device.

That chúng tôi should get in on the fast-growing mobile trading market. Gemini is the safest alternative to Bisq, the best-decentralized exchange. Kraken is an excellent option for experienced traders and those who want to save money. Cash App is suitable for people who wish to trade Bitcoin, but Bitmart is the best choice for people who want to exchange a more comprehensive range of altcoins. Think about what you want to get from this transaction and what you need from it.

What Is The Difference Between A Proxy And A Vpn?

A Virtual Private Network (VPN) is a network that protects user identifications by rerouting the traffic and helps you to connect to a remote computer. If we talk about a Proxy, it also does the same job as like VPN. But there is a difference. This guide helps you to find the difference between a proxy and a VPN. Also, it explains why VPN is a more reliable and stronger service than that of the Proxy, so read on.

Difference between a Proxy and a VPN

In order to abstain from these snooping things, we use a VPN software or a Proxy service that provides a higher level of privacy. Both services allow you to access the internet services anonymously by concealing the Internet Protocol address in various ways.

So, the question arises that if proxy servers and VPN connections perform the same job then why they are called different. Basically, they are different and here the similarities come to end.

What is a Proxy Server?

Proxy software makes it easier for people to overcome Internet censorship. It can make you anonymous on the internet, making the connections more secure and private.

A proxy server is a server that acts as a middle man between your computer and the server that you are trying to access. In this case, the websites can’t detect your original IP address and it seems to come from any other location.

For example, suppose you are currently located in Mumbai city and you need to access the website that is only limited to the people located in the United States. In this case, you need to connect to a proxy server that is located in the United States. After that, connect to that website. That way, the traffic coming from your web browser looks like coming from the remote computer.

Proxy service is quite helpful for the region-restricted websites and it is highly reliable for the task related to low-stakes. As we mentioned earlier, the proxy server uses anonymous network ID, so it bypasses the simple contents filters and services that are based on IP restrictions.

In order to make it more clear, let us take an example. Assume you are five friends and playing an online game where you receive a daily in-game incentive bonus when you vote the game server on a server ranking site. But according to the game policy, you can only vote with your IP address notwithstanding whether other player names are used. Luckily, there is a proxy service using which all the five friends can easily log in their vote and get the in-game incentive bonus. It could happen because the web browser of each person appears to be originating from any other IP address.

Apart from these plus points, there is also some downside to the proxy server. The proxy server is not much reliable for high-leveled tasks. Although, it hides the IP address and works as a mute man lies in the middle for Internet traffic. But, it does not support the encryption protection to encrypt data between your device and the proxy server. Therefore, a proficient and experienced programmer can quickly block sensitive data in transit and keep it.

The proxy service is basically based on an application by application basis. It means that you can’t configure the entire PC while connecting to the proxy.

There are two main types of proxy that are commonly used. These proxy server protocols are HTTP and SOCKS. The HTTP Proxy is the oldest and most wide-spread proxy server. It has been designed basically for web-based traffic so that it could detect the suspicious content easily. The most interesting thing of an HTTP proxy is that it allows you the encryption protection using the SSL certificate, whereas the SOCKS server doesn’t support encryption security.

Read: Free Proxy software for Windows 10.

What is a VPN server?

A VPN or a Virtual Private Network is essential to stay invisible or anonymous on the chúng tôi will encrypt all the data that your device sends so that it will not be hackable. It hides and protects your identity online.

Virtual Private Networks is somewhat similar to the Proxy server, herewith it also offers an extra layer of privacy and security to the internet activity. The VPN functions at the OS level where it occupies the entire traffic connection of the computer it is configured on. That indicates, the VPN captures the network traffic of each application running on your computer that extends far beyond a single web browser.

Additionally, the VPN server encrypts the network traffic between the internet and the computer due to which the whole process passes through an extremely encrypted tunnel. It provides 100% assurance to the protection of data from the Internet Service Providers and the prying eyes of Intruder on internet activity. And that way, sensitive and private information of every single user would remain preserved.

Read: Free VPN software for Windows 10.

VPN vs Proxy

The actual difference between a proxy and a VPN is that a Proxy service lets you hide your IP (Internet Protocol) address and it reroutes the entire network connections anonymous. Whereas a VPN connection has major benefits over the proxy. It not only hides your IP but also provides better encryption to the network between the computer and its servers so that no snoopers or hackers could harm your device.

Artificial Intelligence Vs Machine Learning Vs Deep Learning: What Exactly Is The Difference ?

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

range of applications has changed the facets of technology in every field, ranging from Healthcare, Manufacturing, Business, Education, Banking, Information Technology, and whatnot!

Although these words are familiar and used widely, they are often used interchangeably. But there is a vast difference between all of these.

In this article, we will explore these buzzwords and learn the difference between them.

Artificial Intelligence

Simply put, “Artificial Intelligence is the ability of machines to function like the human brain.”

Whenever we think of Artificial Intelligence, the first thing that strikes our mind is Robots. A few decades ago, ‘Robots’ fascinated us the most with movies showcasing Robots / Superhumans performing insanely tough jobs effortlessly and living on par with humans. Now Robots like Sophia are a reality and we find AI everywhere. Right from robotic vacuum cleaners, virtual assistants like SIRI, robots that perform surgeries in healthcare, robots that write codes, and of course the self-driving cars and trucks – most of these are a reality and the world of Artificial Intelligence is rapidly evolving. Starting with IBM’s chess-playing computer ‘Deep Blue’ which won a chess match against World Champion, to ‘Google’s AlphaGo’, we have seen fascinating discoveries in this AI revolution.

In simple terms, Artificial Intelligence is all about training machines to mimic human behavior, specifically, the human brain and its thinking abilities. Similar to the human brain, AI systems develop the ability to rationalize and perform actions that have the best chance of achieving a specific goal.

Artificial Intelligence focuses on performing 3 cognitive skills just like a human – learning, reasoning, and self-correction.

The evolution of Artificial Intelligence is considered the fourth Industrial Revolution ~ UBS

Experts say, just like how the first 3 industrial revolutions changed the course of the world, the fourth revolution, powered by Artificial Intelligence, IoT and Cloud will surely change the course of humanity and our planet Earth. And enthusiasts are running to learn any AI Course Online.

Let’s have a quick look at the three broad categories of Artificial Intelligence and how we are rapidly evolving in these areas!

1. Artificial Narrow Intelligence

2. Artificial General Intelligence

3. Artificial Super Intelligence

Artificial Narrow Intelligence

Artificial Narrow Intelligence systems are designed and trained to complete one specific task and are often termed as Weak AI / Narrow AI. The chatbots that answer questions based on user input, voice assistants like Siri, Alexa, and Cortana, facial recognition systems, AI systems that search the internet, are examples of Weak AI. They are intelligent at performing the specific tasks that they are programmed to do so.

Narrow AI doesn’t mimic human intelligence, rather it just simulates human behavior based on a set of parameters and input data. Weak AI still requires some amount of human intervention in terms of defining parameters for learning algorithms, feeding relevant training data, and ensuring the accuracy of prediction.

You can think of it as an infant who listens to instruction from adults and performs the functions as directed.

Artificial General Intelligence

Artificial General Intelligence is when the AI systems/machines would perform on par with another human. This also means the ability of the machine to interpret and understand human tone and emotions and act accordingly. This is also called Strong AI and we are still scratching the surface of Strong AI. As Machine Learning capabilities continue to evolve, AI will progress and we will reach there soon.

Artificial Super Intelligence

Artificial Super Intelligence/Super AI is when an Artificial Intelligent machine would become self-aware and surpass human’s intelligence and ability. Although there is so much exciting research happening around this area, there are warnings from scientists as well.

Oxford University Professor and New York Times best-selling author of the book “Superintelligence: Paths, Dangers, Strategies”, Nick Bostrom says,

” The biggest threat is the longer-term problem, introducing something radical that’s super intelligent and failing to align it with human values and intentions. This is a big technical problem. We would succeed at solving the capability problem before we succeed at solving the safety and alignment problem.”

Okay! That’s a lot about Artificial Intelligence!

As we have a fair idea of Artificial Intelligence; are you wondering how the computer system/machine can mimic human actions and perform predictions, automation, and make decisions?

That is where Machine Learning comes into the picture.

Machine Learning

Machine Learning is naturally a subset of AI. It provides the statistical methods and algorithms and enables the machines/computers to learn automatically from their previous experiences and data and allows the program to change its behavior accordingly.

Machine Learning provides many different techniques and algorithms to make the computer learn. Decision trees, Random Forests, Support Vector Machines, K Means clustering – these are just to name a few.

Demand forecasting sales of products, predicting customer behavior, gauging customer sentiments from their social media behavior – these are some use cases where machine learning models are used. Machine learning algorithms work well when the input data is reasonably good enough. When the size of data explodes, we need to look at more efficient algorithms and techniques and that is where Deep Learning finds its hotspot.

OTT platforms like Netflix and Amazon Prime use Machine Learning to recommend movies based on the user’s past viewing data and it constantly improves by learning from past experiences.

Image Source: Scrabbl

In e-commerce, companies like Amazon and Flipkart use Machine Learning to learn the user’s preferences and give product recommendations based on previous purchases and viewing history.

The application of Machine Learning in the real world is humongous!

Now we have a clear idea that Machine Learning and AI are not just the same. Machine Learning is one of the ways to achieve Artificial Intelligence.

Just like anything else, Machine Learning has its shortcomings and that is where Deep Learning comes into the picture!

Machine Learning models don’t perform very well when the volume and complexity of data increase multifold. They need some sort of human intervention and guidance whereas Deep Learning models learn from data and previous experience and correct themselves progressively.

Let’s look at the next buzzword – Deep Learning!

Deep Learning

Deep Learning can be thought of as the evolution of Machine Learning which takes inspiration from the functioning of the human brain. Deep Learning is used to solve complex problems where the data is huge, diverse, less structured. Deep learning models are built on top of Artificial Neural Networks, which mimic how the human brain works.

Let’s look at the basic functioning of our brain to understand how Neural Networks work. Our human brain has neurons which are the basic functional units of our brain. The neurons transmit information to other nerve cells, muscles, and glands and also receive input from other neurons, enabling the brain to make decisions.

Image by Colin Behrens from Pixabay

Imagine, you are a small kid and you see a pot filled with hot water. When you see it you wouldn’t understand it’s hot unless someone says so. If you touch the hot pot, the nerves in your fingers carry this information to the brain, and the neurons process this information and send the signal back to your fingers and you would sense the heat. Next time you see a hot pot, your brain will remember the previous incidents and will remind you that you will feel hot if you touch it.

And our brain continuously learns from inputs from the environment and previous experiences and makes the best possible decision in every scenario. This is pretty much what Deep Learning does! It learns progressively from raw data and previous experiences and corrects itself without explicit programming.

Image Source: DukeToday

Artificial Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks are some of the Deep Learning algorithms used to solve real-world problems.

Self-driving cars and trucks, Virtual Assistants like Alexa, Siri, and Google Assistant, Speech recognition systems, Computer vision, Robotic Surgeries are all interesting applications of Deep Learning.

” At the beginning of 2023, the number of bytes in the digital universe was 40 times bigger than the number of stars in the observable universe” ~ World Economic Forum

To summarize, a lot of AI systems are powered by Machine Learning and Deep Learning algorithms. AI is achieved through Machine Learning, and Deep Learning and they are not the same.

I hope this article gave you a fair idea of Artificial Intelligence, Machine Learning, and Deep Learning.

If you would like to drop your thoughts or connect with me on LinkedIn, here is the link- LinkedIn

Happy learning!

The media shown in this article are not owned by Analytics Vidhya and is used at the Author’s discretion. 

Related

Sas Vs R: What Is Difference Between R And Sas?

What is SAS?

SAS stands for Statistical Analysis Software which is used for Data Analytics. It helps you to use qualitative techniques and processes which allows you to enhance employee productivity and business profits. SAS is pronounced as SaaS.

What is mean by R?

R is a programming language is widely used by data scientists and major corporations like Google, Airbnb, Facebook etc. for data analysis.

R language offers a wide range of functions for every data manipulation, statistical model, or chart which is needed by the data analyst. R offers inbuilt mechanisms for organizing data, running calculations on the given information and creating graphical representations of that data sets.

Google Trend SAS vs R

KEY DIFFERENCE

SAS is commercial software, so it needs a financial investment, whereas R is open source software, So, anyone can use it.

SAS is the easiest tool to learn. So, people with limited knowledge of SQL can learn it easily; on the other hand, R programmers need to write tedious and lengthy codes.

SAS is relatively less frequently updated, whereas R is an open-source tool, continuously updated.

SAS has good graphical support, whereas the Graphical support of the R tool is poor.

SAS provides dedicated customer support, whereas R has the biggest online communities but no customer service support.

Why use SAS?

Access raw data files and data in an external database

Analyze data using statics, descriptive, multivariate techniques, forecasting, modeling, and linear programming

Advanced analytics feature allows you to make changes and improvements in business practices.

Helps businesses to know about their historical data

Why use R?

R offers a useful programming constructs for data analytics like conditionals, loops, input and output facilities, user-defined recursive functions, etc.

R has a rich and expanding ecosystem and plenty of documentation available over the internet.

You can run this tool on a variety of platforms including Windows, Unix, and MacOS.

Good graphics capabilities Supported by an extensive user network.

R Vs Sas Stackoverflow Questions

History of SAS

SAS was developed by Jim Goodnight and John Shall in 1970 at N.C. University

Initially, it was developed for Agricultural Research.

Later, it expanded to a gamut of tools to include Predictive Analytics, Data Management, BI, among others.

Today 98 of the world’s top companies in fortune 400 uses SAS data analytical tool for Data analysis.

History of R

1993- R is a programming language developed by Ross Ihaka and Robert Gentleman

1995: R first distributed as an open-source tool under GPL2 license

1997: R core group and CRAN founded

1999: The R website, chúng tôi launched

2000: R 1.0.0 released

2004: R 2.0.0 released

2009: First edition of the R Journal

2013: R 3.0.0 released

2024: New R logo adopted

SAS Vs. R: Key Differences

Differences between SAS and R

Parameters SAS R

Availability / Cost SAS is commercial software, so it needs a financial investment. R is open source software, So, anyone can use it.

Ease of Learning SAS is the easiest tool to learn. So, people with limited knowledge of SQL can learn it easily. R programmers need to write tedious and lengthy codes.

Statistical Abilities SAS offers a powerful package which offers all types of statistical analysis and techniques. R is an open source tool which allows users to submit their own packages/libraries. The latest technologies are often released in R first.

File Sharing You can’t share SAS generated files with another user who does not use SAS. Since anyone uses r, it is much easier to share files with another user.

Updates SAS relatively less frequently updated. R is an open source tool, so it is continuously updated.

Market Share Currently, SAS is facing stiff competition from R, and other Data analytical tool as a result market share of SAS is gradually declining. R has seen exponential growth in the last past five years with its increasing popularity. That is why its market share is increasing rapidly.

Graphical Capabilities SAS has good graphical support. However, it does not offer any customization. Graphical support of R tool is poor.

Customer Support SAS provides dedicated customer support. R has the biggest online communities but no customer service support.

Support for Deep learning Deep Learning in SAS is still in its early stages, and there’s a lot to work for before it matures.

Job Scenario SAS analytic tool is still the market leader as far as corporate jobs are concerned. Many big companies still work on SAS. Jobs on R have been reported to increase over the last few years.

Salary Range The average salary for any SAS programmer is $81,560 per year in the U.S.A. The average salary for an “R” programmer” ranges from approximately $127,937 per year for Data scientists to $147,189 per year.

Best features

Variables

Mixins

Nested rules

Maintainable

Functions

Data analysis

Graphics and data Flexible statistical analysis

Highly interactive

Famous companies using Airbnb, StacShare, Asana, Hubspot Instacart, Adroll, Opbandit, Custora

TIOBE Rating 22 16

Feature of R

R helps you to connect to many databases and data types

A large number of algorithms and packages for statistics flexible

Offers effective data handling and storage facility

Collect and analyze social media data

Train machines to make predictions

Scrape data from websites

A comprehensive and integrated collection of intermediate tools for data analysis

Interface with other languages and scripting capabilities

Flexible, extensible, and comprehensive for productivity

Ideal platform for data visualization

Features of SAS

Operations Research and Project Management

Report formation with standard graphics

Data updating and modification

Powerful Data handling language

Read and write almost any data format

Best data cleansing functions

Allows you to Interact with multiple host systems

The Final Verdict: R vs SAS

After comparing some main differences between both these tools, we can say that both have their own set of users. There are many companies, who prefer SAS because of data security issues, which show despite a drop in a recent year, there is still a huge demand for SAS certified professionals.

On the other hand, R is an ideal tool for those professionals who want to do deep cost-effective Data analytics jobs. The numbers of startup companies are increasing all over the world. Therefore, the demand for R-certified developers is also increasing. Currently, both have equal potential for growth in the market, and both are equally popular tools.

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