This article introduces and summarizes the data differences between the SAS and Python programming languages. Speaking of SAS and Python, they are very famous languages as candidates for languages that data scientists should learn when working. Both are specialized in data analysis, so both are recommended, but each has different features, so I compared them.
- What is SAS? What kind of programming language is it?
- What is Python? What kind of programming language is it?
- What are the differences between SAS VS Python?
- Can I become a freelancer?
What is SAS? What kind of programming language is it?
SAS is an abbreviation for Statistical Analysis System, and this system is statistical software developed by an American company called SAS Institute. SAS was originally used as analysis software, but as demand for it has emerged commercially and in various industries, it has come to be used for system development as well. Nowadays, it is used primarily in the pharmaceutical industry, but also in the finance, insurance, communications, distribution, and internet industries.Recently, it has been used not only for data analysis, but also for system development and data processing. It looks like this.
What is Python? What kind of programming language is it?
Python is a programming language developed by Dutchman Guido Van Rossum. Python is a highly versatile packaging language that can be used in a wider variety of fields than SPSS, such as web development, data analysis, machine learning, and modeling. Perhaps for this reason, it is a language that is widely used by everyone from programmers to data scientists, and its commercial demand is much higher than that of SAS. When you use it, you will see that it is different from SAS.
What are the differences between SAS VS Python?
When considering the differences between SAS VS Python, you need to look at it from various aspects. Below is a summary of the votes. When it comes to learning in general, creating things using Python is overwhelming. From that point of view, SAS is focused on industries and companies. The usage of variables and functions is also different, so the functions and implementation details are also different between the two.
|Demand for system development
|Demand for data analysis
|number of job openings
|Average annual income (company employee)
|Average annual income (freelance)
|number of technicians
|Main industries with demand
Both can be described as very easy in terms of programming difficulty, so both are relatively easy to learn. Therefore, it can be said that it is a recommended language for beginners. Since you can run the code you write immediately, you can study in real time while checking the program’s behavior. SAS is not open source like Java, and its basic operations and configuration are quite unique. In detail, data and proc steps are the basics, and from a user’s perspective, it can be said to be quite unique.
Demand for system development
Python has an overwhelming advantage in terms of demand for system development. Python is used in a wide variety of applications, including web application development, AI development, and blockchain technology development, so it is in extremely high demand as a programmer. You can also browse libraries and easily perform analysis by selecting them.
On the other hand, SAS is software specialized for data analysis and statistical analysis. SAS system development is rare, but the number is small. In terms of SAS system development, there is extremely high demand for statistical analysis and data management in the pharmaceutical industry. It uses an unusual database called SAS dataset, so it may be difficult to use it at first.
Demand for data analysis
Demand for data analysis is very high for both. Therefore, most data scientists learn one or the other language and actually use it in their work. You can install each framework environment for free online, learn about it, and solve problems. Since the software is used all over the world, you can find many study methods online. Once you acquire the skills to use the tools, you can work as a person in charge and earn a high salary. Since we use statistical methods, we will refer to multiple types of methods.
number of job openings
The number of job openings is overwhelming for Python. Python is overwhelmingly more in demand, whether it’s a full-time employee or a freelancer. On the other hand, SAS is a full-time employee who mainly works in pharmaceuticals, finance, and insurance. In addition, there is demand in communication, distribution, etc., but it is quite a niche. In the case of SAS, it’s a bit difficult to find a job, but the rarity value is high, so the unit price goes up.
average annual income
The average annual income is higher in SAS. This is an industry where pharmaceuticals, finance, and insurance are the main industries and have money, so remuneration tends to be high. Python is mainly in the IT industry, so the annual income is inferior. However, when it comes to freelancing, both are not so different. Some good engineers earn over 10 million a year.
Python is probably the hottest language in the world right now, but that’s because we still don’t have enough engineers. Since it will increase rapidly in the future, the unit price will gradually fall due to the relationship between supply and demand. On the other hand, SAS is pretty niche, so I don’t think it will go up or down in value. SAS is more niche in demand, but I think it will survive quietly and be stable.
number of technicians
As explained above, the number of engineers at SAS is overwhelmingly small. There are many people using SAS in the pharmaceutical, finance, and insurance industries, but there are very few people who use SAS outside of these industries, making it valuable. Since the price of the product is very high, there are a limited number of companies and universities that can use it. Python is already in extremely high commercial demand, is available for free, and has a large number of engineers, so it is expected that the number will continue to grow.
Main industries with demand
In the case of SAS, the main fields are pharmaceuticals, finance, and insurance. In addition, the demand for data scientists is also in industries such as IT, communication, and distribution, but the number of job openings is small. Python is in high demand in the IT and web industries. However, it is also used in other fields.
Can I become a freelancer?