Data Science Career Opportunities Are More Promising, Non-IT Students Can Be Data Talents!

Tangerang – The increasingly dominating career opportunities in the data industry also impact the increasing interest in studying the field of Data Science. As a form of multidisciplinary science, Data Science has three main knowledge: business knowledge, statistics or mathematics, and computer science. Taking the theme Introduction to Data Science, DQLab held an online live session with Code Girl and STBA Lia’s friends on Thursday, August 4, 2022. This live session was hosted by Saraswati, a Business Intelligence at Bibit, also a student without an IT background.

Discussing the importance of Data Science in the era of big data as it is now, Saraswati, nicknamed Saras, explains why we need to study Data Science. She shared that Data Science has good career prospects, high demand, increases creativity, and can make you free to work anywhere. 

Saras also added that according to Data from Digital Around The World (2021), there are 66.6% of the total population uses mobile phones. Various human activities using mobile phones have produced large amounts of data or data. Automatically the people needed to process the data will be more and more specific.

Not from an IT or mathematics background, Saras studied Post Harvest Technology at ITB. This is in stark contrast to the profession she is currently in. Even so, she revealed that she greatly desired a career in Data Science.

“I want a career in Data Science. During my thesis defense, I took part in training and Data Science classes. During my internship, I also participated in the KOMINFO x DQLab training, namely the Professional Academy PROA program. From there, I continued to learn about Data Science until now, and I can work as a Business Intelligence at Bibit,” Saras said.

According to Saras, there are many interesting Data Science professions with backgrounds according to our interests. As a Business Intelligence, she revealed that her most important and necessary competence is to hone her business domain knowledge and data analytics skills.

“Well, I’m a business intelligence person, so I learn more about business knowledge and data analytics, such as coding. If you have friends interested in mathematics and computer science, you can become like AIs, like making algorithms,” Saras said.

For Saras, the essence of all Data Science professions is that we can process data to produce insight, and that information can be used to solve a problem. She shared that there are many roles in data science. She also emphasized that learning data science does not mean that you have to become a Data Scientist. Data Analyst, Data Engineer, Database Administrator, Machine Learning Engineer to Business Intelligence are also professions based on Data Science.

Saras also gave tips on studying Data Science for participants with non-IT backgrounds through this live session. She explained that it is necessary to learn the basics of Data Science first. This can be done by taking courses such as DQLab. In addition, creating data projects and joining the Data Science community can also help in learning Data Science.

“If you want to learn Data Science, especially a non-IT background, my advice is to start with why, how, and timeline. So we can know what profession we really want to be in and know our own learning path,” Saras said, closing the session.

A career in data does not have to have an IT background. Everyone can become data talents by honing Data Science skills with DQLab.

By Lilis Theresia Saragi Turnip | DQLab

English translation by Levina Chrestella Theodora

Kuliah di Jakarta untuk jurusan program studi Informatika | Sistem Informasi | Teknik Komputer | Teknik Elektro | Teknik Fisika | Akuntansi | Manajemen| Komunikasi Strategis | Jurnalistik | Desain Komunikasi Visual | Film dan Animasi | Arsitektur | D3 Perhotelan , di Universitas Multimedia Nusantara. www.umn.ac.id