The development of an increasingly advanced era is also accompanied by the use of data that is used to carry out business development. Did you know that data scientist is one of the most needed professions nowadays. So what exactly is data science? Data science is a data processing capability that will later be used to advance and develop a business.
Are you interested in discussing it further? If you are interested, then you have to read and understand this article to the end! Because Matob will invite you to discuss examples of data science and also the benefits of data science. Let’s start by discussing the meaning first!
Data Science is a Science
Data science is a science that consists of several skills at once such as programming, mathematics, and statistics. The purpose of this skill is to find important information or knowledge from data. Now, people who are experts in this field usually use an algorithm called machine learning or can be called machine learning. This machine learning algorithm is used to create artificial intelligence obtained from images, text, video, audio, and so on.
Later the artificial intelligence system will be used to replace human tasks which are considered quite heavy for ordinary human intelligence. The data that has been successfully processed by artificial intelligence can help analysts create the right business strategy and also find a solution to a problem. You could say that data science is a science that can make it easier for researchers to obtain information. With that in mind, what are the benefits of this data science? Check out the benefits of data science in the next point!
What are the Benefits of Data Science?
Data science is one of the important sciences needed in today’s digital era. We know that both small and large businesses still need data in their implementation. In business, the benefits of data science are quite significant, especially for studying customer thinking patterns. With existing data and the ability to get information from that data, you can create innovations, improve the products or services you provide, and also solve problems in your business. Besides that, what are the benefits of data science?
- Help to find and determine what features or products are really needed by customers and potential customers.
- Can predict current and future habits and trends by reading customer behavior.
- Creating a suitable business strategy.
- It can also help evaluate every running business process.
We can conclude together that the benefits of data science are very vital and needed by businesses in the digital era like today. Therefore, people who are skilled in this field are like diamonds in a pile of stones. Currently, there are many examples of data science that are applied in various fields. What are they?
Example of Data Science that Has Been Applied
At least for now Matob will provide examples of data science which are currently being applied to various fields that we encounter everyday. Here’s an example.
1. Sports field
First, an example of data science is from the field of sports. Who would have thought that in the world of professional sports the application of data science would also have a big contribution. How come? Where is it applied? Let’s take an example in the field of football. Some examples of applied data science include:
Final result prediction
The final result or match score is an interesting thing to discuss. Have you ever thought that the final result of a match can be predicted and is an example of data science. Although the results are not 100% accurate because there are several influencing internal and external factors.
Select and monitor player progress
Recruitment of players is not easy for a team. You don’t want the recruited players to burden and harm the club, do you? For this reason, data science is a solution to overcome this problem. By collecting and analyzing data on the players to be recruited which of course will affect the final result. This data can be in the form of medical history data that can be used as material for analysis.
Developing business within the club
Not only focusing on sports, a club can also be used as a place to do business. Each club has its own fan base. Therefore, an example of data science is analyzing the data of the fans to determine what business strategy to carry out, whether in the form of merchandise, fan t-shirts, or various activities that involve the fans.
Data Science is awesome, you can read this article Science and the World Cup: how big data is transforming football .
2. The health sector
The health sector is the biggest example of data science and became the first application of data science in 2008. Therefore you will easily find examples of data science in this field. What are its applications in the medical world?
Analysis in medical photos
The first is that it can assist in the process of medical photo analysis. In its development there are various medical aids that are used to detect human internal organs so that they can facilitate the healing process and find the best solution for the healing process.
Actually, patients or customers may not have to do a check-up or medical examination directly. Therefore, currently a mobile application has begun to be developed which can make checking online easier. So, this is an example of data science because we can analyze what kind of application needs customers want, whether it’s an application equipped with a reminder to take medication, an application equipped with AI technology, or something else.
3. Financial sector
The next example of data science comes from the world of finance. We all know that the biggest challenge in this field is the problem of fraud which can be financially detrimental. With these challenges, many banks use data science to classify, group, and also divide fraud pattern data into various categories. This is of course to avoid and minimize the possibility of fraud and fraud. In addition, many experts also add some special code to detect various fraud patterns applied.
The field of e-commerce also applies this knowledge to determine selling prices or dynamic pricing. This is done to divide and identify the segments of each customer group in order to get product offerings that are right on target. This calculation is usually based on many factors such as property reviews, lead time, and facilities provided. also read top e-commerce platform in Indonesia
5. Field of education
The last field that has adopted this knowledge in its implementation is the field of education. What are the applications of data science in education?
The curriculum is teaching material that will be given to all students. Therefore, the curriculum must have a clear and relevant vision and mission for the future. Currently, the education sector is starting to utilize data science to update the curriculum to make it more relevant to the times.
In the field of education, especially schools or campuses must be able to attract the best students or students so that the vision and mission can run smoothly. Therefore, data science is very useful for finding programs that are suitable for certain groups.
What Jobs Make Use of Data Science?
There are several occupational professions that utilize this knowledge. Here are some of the professions.
1. Data scientist
The profession that occupies the first number is a data scientist. Their main responsibility is to collect and analyze unstructured and structured big data. The next one must interpret the results that have been obtained for the needs of a business. The role is quite complex by combining several sciences such as statistics, computers, and mathematics which will be used for data analysis and modeling.
2. Data analyst
Many business sectors require a data analyst, such as the financial, business, legal, medical, government, and science sectors. Therefore, if you are interested in this knowledge, you can try the profession of data analyst. In essence, their job is to collect and interpret data with the aim of solving customer problems.
3. Data engineer
What fields require data engineers? The answer is in the field of deep learning as well as machine learning. Both of these fields will not be successful if the data engineer does not process and distribute the required data. Its role is to design a system that will be used to collect and analyze data on a large scale.
4. Data storyteller
The last profession is data storyteller. Does that mean you’ll be responsible for telling stories later? Hmm, almost the same. So a data storyteller is a person whose role is to find various points from many sources and then identify them with the aim of drawing conclusions. After that they also have to be able to visualize data by determining the best way to be easily captured and remembered by customers and stakeholders. one of the tools for data visualization is powerBI.
Interested in Learning Data Science Deeper?
Indeed, when talking about data, it will be closely related to complexity and requires special foresight and expertise. Therefore, not just anyone can control and analyze data. Therefore, there is a science that consists of computer science, mathematics, and also statistics which is commonly known as data science.
There are many examples of data science that have been applied, from the health, sports, education, e-commerce, and financial sectors. So, if you are really interested in this knowledge, then there are 4 professions you can try, such as data engineer, data analyst, data storyteller, and data scientist. Interested in trying one of these professions?