Firdaus Afifi Md Isa
Lim Yong Hui
Supiah Selamat
Wee Ming Qiu

IN late 2013, big data analytics was proposed as a critical enabler to drive business innovation that leads to productivity gain and information technology (IT) industry growth.

Prime Minister Datuk Seri Najib Razak approved the proposal at the 2013 Multimedia Super Corridor Malaysia Implementation Council Meeting and endorsed the decision to develop the National Big Data Analytics framework.

The framework includes strategic intent, priorities and imperatives to drive big data analytics adoption in both the public and private sectors.

Malaysia Digital Economy Corporation Sdn Bhd (MDEC) was appointed the lead agency to spearhead the initiative, which aims to position the nation as the leading big data analytics solutions hub in Asean.

To achieve this, the country requires a healthy ecosystem, enabling businesses in both the private and public sectors to adopt big data analytics, a process of examining data sets to draw conclusions on the information they contain with the aid of special systems and software.

Wan Nor Mafudah explaining Capital Structure, a traditional theory, during a question-and-answer session in class.

While data science requires knowledge of programming, mathematics and statistics, for example, the field should not be restricted to computer scientists and mathematicians only, but should also be open to those from disciplines such as finance, biotechnology and social sciences.

As one of five key enablers of the big data analytics ecosystem focuses on talent, the target is to nurture 20,000 data professionals including 2,000 data scientists by 2020.

In terms of talent development, 4,949 talents were developed before 2017. The country has developed 5,804 talents so far.

As of the end of last month, 768 talents were developed via professional development programmes and 87 were nurtured by universities.

Of the remaining 14,196 data professionals out of the 20,000 to be developed by 2020, 17 per cent are expected to graduate from universities and the remaining 83 per cent from professional development programmes.

The Asean Data Analytics eXchange (ADAX) was set up early this year to produce more data professionals and data scientists.

ADAX is a regional platform to connect communities, enterprises, start-ups, academia and working professionals in a central location to drive data-driven innovation.

Chief executive officer Sharala Axryd said that at the crux of ADAX is the innovative talent development programme where professionals and fresh graduates can pursue data science courses.

Aspiring data scientists as well as companies are mentored by ADAX resident scientists using real-life cases and data sandboxing.

“ADAX’s mission to nurture data professionals for the Asean region has gone from strength to strength since its launch,” said Sharala.

ADAX hosts a technology showcase where big data analytics players can show-and-tell their latest technologies as well as utilise the data sandbox to develop solutions.

It also facilitates partnerships between start-ups and world-class accelerators.

The country has increased the number of data professionals through the Data Star programme, a public-private partnership initiative.

“It is a data science finishing school designed to fast-track the development of world-class data professionals who meet industry needs.

“A joint effort between ADAX, MDEC and industry players, it will help Malaysia to produce 20,000 data professionals in four years’ time, a goal set by the government in 2015.

“We look forward to working with renowned industry players to further develop the skillsets necessary to tackle big data head-on.”


A year ago MDEC chief executive officer Datuk Yasmin Mahmood mooted the idea of a virtual platform to enable collaboration and the exchange of talent, ideas and data.

“Several companies in Malaysia with a strong Asean presence had shown high interest in recruiting data professionals.

“Candidates with doctoral degrees in mathematics were suggested. They excel in modelling and programming but they are not keen on business communication with senior executives.

“I thought to myself that if we can’t get them, we make them. The mantra is talent, talent, talent,” she said.

ADAX is looking at ways to get more students interested in data science. “We have to improve awareness of the field and develop an attractive image to draw students. We expose students to the industry through talks.”

However, Sharala said it is a challenge to nurture an analytical mindset and critical thinking.

Moreover, one needs to not only excel in maths and programming but also communicate an idea and visualise it in a way that a layman will understand.


A six-month finishing school course for graduates, the Data Star programme includes two months of intensive data science enablement and mentorship with experienced data scientists and placement with industry partners.

“We work with universities and industry partners to fast-track the development of industry-ready data professionals.

“We collaborate with multiple partners which offer placements such as Celcom, Leo Burnett, Fusionex and Fave,” said Yasmin.

The learning path is curated to align with the Data Professionals Skills Framework, a platform that supports data and analytics knowledge development with a focus on three primary scopes — data engineer, data analyst, and data scientist.

“We provide students with the basic skillsets for each of the knowledge areas such as research analytics and algorithms.

“Our courses include lectures, lab and interactive sessions, and hands-on programming. Each learning path includes mentorship, a project presentation and soft skills development,” added Sharala, who has more than 15 years of experience in the telecommunications field.

Graduates with doctoral qualification and Master and Bachelor of Mathematics, Statistics, Computer Science, Actuarial Science, Engineering, Economics and Science are eligible to apply.

“Knowledge of programming is an advantage.”

The first intake of 48 students was on July 24 and more than 50 per cent are placed with industry partners.

Students undergo a Data Science Track with seven modules for 42 days.

Thereafter, they will be familiar with all the data science steps: data collection, cleansing, processing and modelling, evaluation of a model, visualisation of data and communicating the results.

Students get an in-depth understanding of data science concepts. A large part of the time is spent in labs where theories are put into practice.


Data Star student Firdaus Afifi Md Isa, 26, also a Public Service Department scholar, graduated from University of Malaya with a Master of Computer Science, majoring in Computer Security.

“My master’s programme supervisor encouraged me to apply for the Data Star programme.

“After two months, we completed five modules of theory and projects in the lab.

“The trainers taught the fundamentals before touching on more complex topics. They covered every aspect in detail,” said Firdaus Afifi, who will intern for four months at Petronas.

He won the grand prize at the Malaysian Administrative Modernisation and Management Planning Unit 48 Hours Open Data Hackathon 2016 and clinched third place at The Institute of Electrical and Electronics Engineers Malaysia Final Year Project Competition in 2014.

Firdaus Afifi co-authored a research article on Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware that uses a hybrid method to find optimum parameters to facilitate mobile malware identification.

He has also participated in several online training courses such as Data Science Massive Open Online Courses facilitated by MDEC to upskill himself.


During Supiah Selamat’s tenure as a research assistant at Universiti Kebangsaan Malaysia, she encountered a huge amount of data.

The 31-year-old realised that she needed to improve her knowledge of data science.

“I applied for the Data Star programme because I wanted to challenge myself. I seemed to be at the right place at the right time as I was about to finish my term as a research assistant.”

A Master of Science in IT Management graduate from Universiti Teknologi Malaysia, Supiah always had an interest in the technical field.

With eight years of working experience under her belt, she has a solid footing to pursue the programme which covers programming, database and statistical analysis.

“Even though I have the fundamentals in certain aspects of data analytics, I struggled in the beginning to familiarise with some of the modules, especially statistics. I had to put in a lot of effort,” said Supiah, who is in her first month of internship at Fusionex.


Prior to joining the Data Star programme, Lim Yong Hui, 25, has attended several workshops relating to mathematics. She has also acquired basic programming skills and learnt AutoCAD software and 3ds Max (3D modelling and rendering) software

A Master of Science in Mathematical Modelling graduate from Universiti Sains Malaysia (USM), Lim has a head for numbers.

“I attended a talk by ADAX at USM and knew that I needed to up my game. While the programme is a stepping stone to realising my dreams, picking up programming language can be a challenge,” she said.

“The programme is a good platform, especially for beginners like me.”

Lim has co-published a paper on simulated tsunami run-up amplification factors on Penang island for preliminary risk assessments.


Wee Ming Qiu, a Bachelor of Computer Science (Honours) in Software Engineering graduate from Tunku Abdul Rahman University College, developed an interest in data science at an early age.

The 22-year-old enjoys collating data and getting insight from it.

“The Data Star programme is a platform to jump-start a career in data analytics as it offers placement at major companies.

“I enjoy the projects with guidance from the mentors,” said Wee, who has enrolled in online courses such as Coursera and Udemy.

Last year, he participated in the technology showcase Wi-Me 2.0 and was Best Innovation first runner-up and Best Poster second runner-up.

He has interned at Fusionex, which exposed him to programming software, and now works at Celcom.


The analytical mindset is the most important trait, according to Sharala.

“We are looking to raise awareness of data science among students as the profession can be an avenue for success.

“ADAX wants to make a difference to companies through the creation of a talent pool to steer Malaysia towards a highly skilled nation.”


Data Engineering

Aim: To enable participants to understand the importance of data management and realise value from it

Duration: 25 days

Modules: Six

Data Analysis

Aim: To equip participants with the ability to run analysis using R programming language, and communicate and visualise findings

Duration: 21 days

Modules: Seven

Data Science Track

Aim: Teaches participants to think in a data-scientific way, conduct or approximate experiments on business activity, analyse data rigorously, develop predictive models and monitor model outputs

Duration: 42 days

Modules: Seven

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