EXCLUSIVE - Enhancing creation and exchange of big data ideas and talent through physical infrastructure at ADAX Malaysia
Photo credit: ADAX
In late March, OpenGov reported on the launch of the ASEAN Data Analytics Exchange (ADAX) by the Malaysia Digital Economy Corporation Sdn. Bhd. (MDEC). ADAX is described as the world’s first physical data exchange platform, seeking to be the deﬁnitive portal and resource hub for Big Data Analytics (BDA) in Malaysia and ASEAN region.
We had the opportunity to converse with Ms. Sharala Axryd (above), the Chief Executive Officer (CEO) of ADAX and learn about the idea behind ADAX and the plans going forward. Ms. Axryd explained the need for ‘physical’ infrastructure and emphasised the importance of inculcating an analytical mindset in students in schools and universities and exposing them to data science at an early stage.
How did you become involved in data science training?
I am a telecommunications engineer and the first company that I started was focused on the telecommunication industry. Around 2013, during a project for telcos, we stumbled upon a situation where the telcos’ network KPIs (key performance indicators) were looking good but they were losing customers to the competition.
We had to understand customer sentiment, what people actually thought about the network. That was our trigger for getting into big data analytics. I was given a list of candidates I should look for, with like double PhDs in mathematics. These mathematicians were great at modelling and probably programming, but they were not interested in communications or talking to C-level executives about business.
Because I was running a very hands-on technical training company (ULearn), I thought to myself that if we can’t get them, we make them. We started The Centre of Applied Data Science (CADS).
I contacted the The Data Incubator. They have an intense boot camp accelerator course for data scientists. I reached out to Harvard Business School (HBS) Executive Education to run a customised BDA programme for decision makers. This was the first time, the HBS programme was brought outside the US. The collaboration was between CADS and HBS. MDEC and HRDF were stakeholders, with MDEC facilitating and HRDF putting in the funds.
How did the idea for ADAX come about? Where does ADAX fit into the current data landscape in Malaysia and ASEAN?
Around a year ago. Dato’ Yasmin, the CEO of MDEC, had this idea for a virtual platform, that could enable collaboration and the flow and exchange of talent, ideas and data.
I was running CADS as a centre of excellence dealing with anything and everything about data science be it talent, ideas or disruptive technology.
We got together and our ideas synced. It had to be ASEAN because I think there are several companies in Malaysia with a strong ASEAN presence and they have already shown high interest in getting data professionals.
Public private partnerships are going to be crucial for the success of ADAX. ADAX is by the industry, for the industry, with the government acting as facilitator. Private companies will contribute data. Academia can provide the right talent equipping people with skills fitted to industry requirements. The technology and training partners would be the specialists enabling the transfer of talent and placement in industry.
What is the demand like from the government side?
For the public sector also the demand is huge. The challenge in government is cleansing the data. There is data from many, many years ago. Different agencies and ministries within government have been taking their own initiatives, progressing gradually. But the process has definitely started.
What are the areas of focus for ADAX during the first year?
The mantra is Talent, Talent, Talent. In four years, we have a mandate to churn out 20,000 data professionals. During the first year, we plan to train at least a 1000 and from there we will accelerate towards the four-year target.
We are working with universities, encouraging them to embed analytics into their curriculum. We are trying to speak to companies willing to upskill their employees. We want to churn out more data professionals, more organically.
We are looking at partnering with world-renowned academic institutions. We already have HBS and The Data Incubator. We have three more possible partnerships on data analytics in the pipeline.
At the other end, we are 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.
Being a female CEO and entrepreneur, influence more females to take up these professions is an issue close to my heart. We have plans to work closely with stay-at-home moms. They might have quit their professions to take care of their kids. If the kids are grown up now, we want to get them back. We are working with a lot of organisations for that.
Can you tell us about some of the ongoing initiatives in relation to start-ups and open data?
Right now, we are running the ASEAN data accelerator. There are 10 SMEs involved and four of the companies come from ASEAN. We are running that with ODI, the Open Data Incubator in ADAX. It’s a 6 month programme, and we are 2 months into it. We are going to have another one, once this is done.
Under ODI, we are seeking to get the private sector to open up their data. Some telcos and other service companies have committed to can give us some data, so that the data scientists that we train could use the data as a prototype to work on. SMEs can also come up with ideas based on the data that’s available. We have already started those initiatives.
Why has ADAX been established as ‘physical’ infrastructure? What does it mean?
In this modern era, everything should and would be available virtually.
But we felt the need for a physical place where people could meet and exchange ideas and techniques and talk about the latest developments in technologies like deep learning, AI. We wanted a place where training could physically happen. We wanted a physical space where student and SMEs could work along with data scientists and prototype and incubate their ideas.
We bring the industry in to talk about their pressing problems. We bring students in to be exposed to ideas and get inspired. It is possible to do all this virtually, but when people attend physically and network, it is much more effective.
Recently, I met the Vienna Data Science Group. The members are hundreds of PhDs in maths, computer science, who work in some of the biggest companies as head of data science. And they meet up on weekly or bi-weekly basis. Someone working in the Financial Services Industry (FSI) would be using totally different techniques from someone in healthcare. And these meet-ups are the best place for them to exchange techniques, stay up-to-date.
It’s the same with the incubators at HBS or Stanford. People physically sit there for the first year or two to build something. It could be done virtually but it’s not the same.
What are the primary challenges you see in the data science field?
First is having the data, the right, cleaned data. For that you need data engineers. The scientists will then ask the questions, find answers, experiment. They might want to ask 20 different questions and look for 20 different solutions. And not all of that might be applicable to business.
A lot of MNCs expect the data scientists to come in and solve all the business problems. It doesn’t automatically happen that way. That’s an interesting challenge right there, churning out data scientists to ask the questions, looking at business challenge and then looking if the data is available or you need to collect data. You might find that the data is not sufficient to make a conclusion. Then we have to find ways to collect extra data and maybe wait for a year to have enough samples. One of the challenges, tactically is that.
The second challenge to train people with the analytical mindset and critical thinking in the universities and schools. Moreover, just being academically great in maths and programming is not enough because you should be able to communicate your idea, visualise your idea in a way that a layman would be able to understand. That’s tricky. That’s why globally we are not producing enough of those people because I don’t think that combination of science, maths and personality is easily available.
What kind of background do you think is required for data science training?
There’s this sentiment among some data scientists, that only computer science graduates are qualified to become data scientists. To become a data scientist, you need to have a great combination of programming and maths (Statistics, probability) but having said that, it shouldn’t be restricted to computer scientists and mathematicians. They are great candidates no doubt.
But academia is looking at infusing data science topics in their undergraduate programmes in all domains, from finance to biotech to social sciences. So, I believe it could be anyone with a STEM background, who knows programming and math.
The analytical mindset is the most important thing in my view. And that’s what we are working to inculcate in students. We are looking to inculcate awareness regarding data science and data professionals among the students as they come out of school.
Simultaneously, parents have to believe that this profession can be an avenue for success. In general I would say the education system in Asia is focused on studying hard and performing well academically. In places like the Scandinavian countries, there is more freedom to be creative and explore. But as a parent I might still feel like my kids go to school to study, not to play. It’s a difficult mindset to change. I might be afraid that my kids will lose out, if they didn’t ace their maths exam.
The World Economic Forum estimates that over half of children entering primary school today will end up working in jobs that have not been created yet. I want parents to be aware that you can never really prepare your child for that. You can only equip them. Probably they will be the ones to come up with those jobs of the future. It’s scary and exciting at the same time.
Where do see ADAX in four years’ time?
We would like to be able to say that we have made a difference to companies through the creation of a talent pool, that ADAX made an impact on the economy, that we have contributed to moving Malaysia towards a highly skilled nation.