Insights on Big Data

By Rachel Lim

The Discovery+ Series is a series of events, delivered through online digital solutions, which give students the chance to speak directly with working professionals, and learn about careers they aspire to enter. Given the developments in the COVID-19 situation, Advisory is keen to provide support to the many students who are experiencing woes in this time of disruptions, by digitalising professional mentorship.

The Discover+ Panel on Big Data, held on 19 January 2021, was graced by

• Lim May-Ann (Moderator), Managing Director, TRPC Pte Ltd;
• Dr. Alvina Goh, Deputy Director of AI Platforms (Data Science and AI Division), GovTech;
• Marcus Tee, Solutions Architect, Microsoft Singapore; and
• Sinuhe Arroyo, Founder and Chief Executive Officer, TAIGER.

Attendees included students at various levels of education with a desire to know the different career paths in Big Data, and how to best position themselves for such roles.

Is it necessary for prospective candidates to have a degree in Mathematics or Statistics, before pursuing a career in Big Data?

While there are some specific roles in Big Data which require candidates to be conservant in Mathematics/Statistics (e.g., analytics, machine learning), many companies in Big Data hire people coming from a wide range of backgrounds and degrees. Typically, many companies in this sector look out for certain characteristics in prospective candidates, such as problem solving skills, the ability to think logically and a willingness to learn. In fact, many companies provide opportunities and internal training for employees to upgrade their skills, for the specific technologies that each company might employ in their workstreams.

While having a technical background is also encouraged, it is not the sole criteria that companies consider when hiring.

What are some important skills that Big Data companies look out for in candidates?

Logical thinking skills and problem-solving skills are highly sought after by Big Data Companies. One should be able to identify and troubleshoot problems that they encounter. Additionally, as jobs in the Big Data field largely involve data analytics, programming and data analytics skills are of paramount importance as well. These are not standalone groups of skills, since one could infer one’s ability to solve problems from one’s programming and debugging ability.

Lastly, as aforementioned, Big Data companies also look out for prospective candidates with an attitude for learning.

Any advice for students who have yet to enter university and are planning to enter the Big Data field?

Firstly, it is important not to constrain yourself on given experiences of pathways. Instead, having an open mind and exploring various segments of work, related to Big Data, can improve your chances of entering the field.

Secondly, building up a digital portfolio (e.g., on GitHub) will be helpful, especially when you are pursuing any career in the future. A digital portfolio showcases your experience on projects and skills to future employers, which can give you a competitive edge when entering the Big Data field.

Lastly, if you wish to enter the technical route, obtaining a technical certification would certainly be useful, as it showcases your programming and logical thinking skills. If you do not have any prior programming background, you may check out the many resources and online courses available on the web.

What programming languages would you recommend to candidates who wish to improve their marketability to employers in the Big Data field?

Java is a good programming language for beginners, along with Python. These are general-purpose languages, with many applications. There are, however, some specific communities that have been built around some languages, which result in more resources for those communities’ use cases in given languages; for example, there are many resources for data science, machine learning and natural language processing for those who can code in Python. Platforms for building data pipelines like Databricks are also becoming more popular, and being conversant in these platforms can help you get ahead. You can also dabble in the Application Programming Interfaces (APIs) put out by big tech companies by creating something simple with them. These are usually free, with minimal barriers to entry (e.g., registering for an API key), and you can work on some very interesting projects with these APIs.

If you do not have a programming background, creating projects in Scratch is not only a good starting point, but is also useful in showcasing your logical thinking abilities.

What are the prospects of the Big Data industry in Singapore?

The Big Data industry is currently still growing with its potential value beginning to be fully realised. It is set to grow tremendously, in terms of the number of fresh graduates joining the field as well as the upskilling of existing professionals in handling and analysing data. Given Singapore’s role as a hub for the transportation of physical goods, along with existing cloud and data infrastructures in place, the country is in a strategic position to be a hub for Big Data. Overall, the Big Data industry is set to have a bright future moving forward.