Description

Definition of Data Science

Data science is a science that is currently on the rise, which is built on the disciplines of mathematics, statistics, and computers. The combination of these disciplines makes data science powerful for processing big data. Data science can help with data processing which includes data collection, data manipulation, and data analysis by modeling data sets to produce information in the form of useful insights and can be used as a guide in making decisions in the future. Data science processes big data which contains both structured and unstructured data. So, not only numeric data but also data in the form of voice, images, text, and so on.

Why is Data Science Important?

Data science is an important science, because small and large businesses rely heavily on data. If the company is not capable of processing data, the business will not have the guidelines for an effective and efficient operating strategy to make a profit.

Today, companies around the world are increasingly recognizing the importance of data science, artificial intelligence, and machine learning. If a business wants to compete and stay relevant, it must be able to implement data science. 

Hal Varian, a Google economist and UC Berkeley lecturer in Computer Science, Business, and Economics, said that being able to retrieve, understand, process, and extract value from data and visualize it is an increasingly important skill in the next decade. Of course, people who have a good understanding of data science will be valuable and much sought after.

Data Science Pillar

Data science can be used for various sciences. However, there are three important pillars that support it, namely:
1. Business

A data scientist who processes data based on data of science must be able to process data into understandable information to help design strategies to solve business problems.

To be able to do this, data science expertise must also be accompanied by a business understanding so that the proposed solution based on data is possible for a business to carry out to achieve its goals.
 

2. Mathematics and statistics

Data science is in dire need of mathematics, because data must be processed quantitatively. Many problems in business can be solved by making analytical models with a mathematical basis. To make it, it takes a deep understanding of mathematics.

For example, algorithms for designing machine learning as an application of data science are closely related to mathematics. Statistics for data science is no less important. Not only understanding classical statistics, a data scientist also needs to understand Bayes statistics.
 

3. Technology

Of course, data science cannot be separated from technology and creativity and intelligence in using technical expertise to solve a problem. Data science is a science that uses large amounts of data and complex algorithms, so it requires deep computer science skills. A data scientist needs to master the programming languages ​​such as SQL, Python, R, SAS, Java, Scala, Julia, and many more. A data scientist must be able to think like an algorithm in solving even the most difficult problems.

Benefits of Using Data Science

After knowing about the basic understanding of data science, you can find out some of the benefits of data science. The benefits of data science are:

1. To improve the quality of failed products so they don't happen again.
2. Can predict a good product or strategy in certain seasons
3. Predict consumer or buyer behavior on company products
4. Make decisions based on existing data in the company.
5. Make the delivery process more efficient by checking the existing data on traffic from the logistics section.
6.   Increase the level of satisfaction of employees of a company based on the feedback data that the company has.
7. For securities companies, the benefit of data science is to make more effective investment decisions for their clients.
8. Classify a high quality product using data from the quality control team.

Examples of Application of Data Science

Data Science has actually was used by companies to help manage their data. They realize that a collection of data that is processed properly will produce information that is useful for the progress of the company. Data science began to be widely heard in 2018. Since then data science has become popular and has begun to be widely applied in various fields because of the benefits it provides. For example in the food industry such as fast food restaurants. By applying data science, we can process sales data such as looking at consumer preferences in choosing food menus based on gender or age to determine the composition of menu packages so that sales of certain items that were previously lacking increase. This can also be applied in the retail industry to determine promotional strategies for certain products so that sales results for these products do not decrease. Apart from the business industry, data science can also be applied in the fields of health, government, and others. An example of the application of data science in the health sector that is most relevant to current conditions is to find out the development of Covid-19 in Indonesia. By knowing the developments, it will be easier for the government to take actions that can contain the spread of the virus, provide insight to the public, especially areas that have had a severe spread of the virus, to take better care of their health, and so on. There is also research that uses data science to help treat cancer. The tools used in data science are machine learning, data mining, deep learning, and artificial intelligence.

Example:

Bibliography

Star, S. N. (2022, June 8). What is Data Science? Definition, Benefits, How it Works, and Examples! Retrieved from makinrajin: https://makinrajin.com/blog/data-science-Jadi/

Lab. (2021, April 11). Definition of Data Science, Examples of Its Application, and Professional Fields Related to Data Science. Retrieved from delay: https://dqlab.id/pengertian-data-science-exemplary-dan-profesi

Rahmalia, N. (2022, January 12). Data Science: Meaning, Benefits, Processes, and Examples of Its Application. Retrieved from glints: https://glints.com/id/lowongan/data-science-Jadi/#.Y3EKPORBzIU.

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