Should You Invest in an Online Master in Data Science?

Data Science

Data science is a growing field that is being adopted in various industries outside the world of technology. The 2020 Global State Of Enterprise Analytics survey by Microstrategy, a pioneer in the business intelligence and analytics industry, found that 94% of organisations believe data and analytics are key to successfully implement digital transformation efforts. This goes to show that data science isn’t limited to just the tech industry, but can be applied across a myriad of sectors.

Choosing to pursue a postgraduate degree in data science will prove to be fruitful in the long run as you’ll not only gain new skills and knowledge, but also a new perspective on the evolving world of data and technology. 

Greater Career Options 

Enrolling in a postgraduate programme is often fuelled by the intention of wanting to scale up the career ladder and explore new roles in different fields and industries. By equipping yourself with an enduring and transferable skill set, particularly related to data science, you’ll be able to access these many windows of opportunity: 

Agriculture

Agriculture is one of the main contributors of gross domestic product (GDP), which is a unit of measurement for a country’s economic output. It’s a massive industry that specialises in livestock, aquatic life, crops and plants, and forestry. 

According to the Department of Statistics Malaysia, all ASEAN countries, except Singapore, saw an increase in contribution to GDP from the agricultural sector in 2020 – further proof of its importance to the economy. 

The output of agriculture is highly reliant on resources, and with data science, farmers and agricultural professionals can better manage their production processes. The implementation of tech-driven processes and decisions allows agriculture professionals to produce larger quantities of food with fewer resources, ultimately fulfilling the rise in demand due to an increasing population. 

  • Is it future-proof - Agriculture is an industry that is recession-resistant. While it may be slightly impacted by a recession, job security is stable as people need food to survive. 
  • Data science in agriculture - A common example of data science in agriculture is using artificial intelligence (AI) to identify insect types and volumes impacting crops which offers valuable insights for enhancing pest management.

Entertainment

The entertainment industry covers a myriad of services, from media and movies to gaming and music. In Malaysia, video-on-demand or streaming services are the most popular form of entertainment services. Statista reported that the number of users in the video streaming segment is projected to amount to 5.4 million by 2027.

Streaming services, such as Netflix, Disney+, and Spotify, collect treasure troves of data from their customers. This is where data science comes into the picture. Data scientists are able to turn that raw data into meaningful insights that can be used to better a platform’s services and offerings, with an example being Netflix utilising data science in its recommender systems.  

  • Is it future-proof? - From a holistic point of view, the entertainment industry can be threatened by a recession as entertainment is the first thing people cut down on during tough times, but it is also one of the first few industries people come back to once the economy improves.
  • Data science in entertainment - Data science plays a crucial role in the entertainment industry. It enhances customer recommendations by analysing viewers' watch histories through recommendation engines. Another key application is personalised marketing. Organisations increasingly prioritise data analytics alongside digital capabilities to refine their services. By leveraging data insights, companies can gain a deeper understanding of their audience and promote more engaging content on social media.

Healthcare

The healthcare industry is no stranger to data science. In fact, the Healthcare Big Data Analytics Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027 report showed that the market value of big data analytics in the global healthcare industry was valued at USD31.8 billion (RM144.4 billion) in 2021 and is projected to reach a market value of USD71.6 billion (RM325.3 billion) by 2027. 

Data science has always been at the forefront of medical advancements. Today, it’s considered an imperative part of the industry, with an increase in enhanced testing technology, mobile applications, and wearables to monitor and track diseases. 

  • Is it future-proof? - Yes. The healthcare industry is here to stay, regardless of the current economic situation. As much as people rely on technology, they will always opt for a consultation with a licensed doctor, compared to being assessed by a robot. 
  • Data science in healthcare - Data science significantly impacts healthcare by monitoring patients and tracking health via wearables like smartwatches. This enables precise predictive analyses, as practitioners can access data reflecting various medical factors. It also enhances medical imaging techniques, such as X-rays, MRIs, and CT scans. With advancements in deep learning, identifying microscopic abnormalities in images has become simpler. Furthermore, machine learning algorithms improve the accuracy of drug discovery processes.

Sports

The sports industry is one that benefits greatly from data science. Data science in the sports industry is commonly referred to as sports analytics, in which data scientists apply their knowledge of data analytics to infer how weather conditions, recent wins and losses, and team circumstances can impact a game. 

The advancements in big data analytics have made acquiring sports data relatively easy. The challenge, however, lies in decoding that data and turning it into actionable insights for sports management teams. Data scientists or sports analysts are able to use predictive analytics to decipher the data collected, paving the way for better decision-making. 

  • Is it future-proof? - The sports industry itself may not be recession-proof, but sports analytics is a different ball game. Regardless of the economic situation, sports games still happen — albeit in an empty stadium. Sports management teams still look to data scientists to analyse their games and track players' performance. 
  • Data science in sports - Sports management teams often employ the use of sports analytics to forecast the outcome of a game. Through sports simulations, coaches are able to run an algorithm that predicts how a specific player will perform in that game and how his or her performance will affect the scoreboard. Similarly, sports management teams also use sports analytics to make scouting decisions. They analyse the player’s statistics and performance results to determine how he or she can contribute to the team’s overall success.

Manufacturing

Data science is shaping how we manufacture products and manage processes. In a commissioned study by Forrester Consulting on behalf of RapidMiner in 2021, it was found that 83% of manufacturers believe that data science initiatives give them an edge over their competition. 

Through data science, manufacturers are able to gather data and convert it into valuable insights that aid in decision-making to maximise profits, minimise risks, and speed up production time. 

  • Is it future-proof? - It’s safe to say that the manufacturing industry is recession-proof, especially for food and pharmaceutical production. Certain manufacturers are even able to grow their business during a recession. 
  • Data science in manufacturing - Data science plays a vital role in manufacturing by managing inventory and forecasting demand. It enables comprehensive control of the supply chain, improving real-time processes such as purchasing and transportation. Additionally, data science optimises pricing by allowing manufacturers to assess the factors influencing product costs, helping them decide whether to price items lower or higher.

Your Path to Data Mastery Starts Here

Data science is a growing field that’s needed in every industry. What used to be limited to those with a background in data and computer science is now accessible to everyone. Those with a non-related bachelor’s degree can pursue a Master in Data Science at Sunway University Online – just complete two prerequisites to be eligible: 

Foundations of Programming

In this subject, you’ll learn the ins and outs of programming languages, particularly Python. Develop and understand how to work with basic Python data types, structures, and collections, and write, run, and debug short Python scripts to perform automated tasks. 

Database Concepts and Principles

Build an understanding of the underlying concepts of data analysis and design. Upon completion, you'll be able to construct and implement databases using relational data modelling, Structured Query Language, and database management systems. 

Still unsure about our Master in Data Science? Here's your chance to get the answers you need. Check out our blog article here, packed with a extensive list of frequently asked questions (FAQs).

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