Big Data. It’s a hot topic in the current conversation centred around future work possibilities and opportunities. The rise of data science has been largely due to the analytical capabilities now demanded by industries across the board.
Concurrently, many industry leaders have noticed a jarring shortage in qualified data scientists and this has led to a surge in the popularity of data science jobs.
Many people are, however, still unclear about the exact definition of data science or how this discipline may possibly be one of the greatest career paths to have surfaced in our increasingly tech-empowered world.
Sharala Axryd – founder and chief executive officer of the Center of Applied Data Science (CADS) – has been paving the way for greater exposure around data science and its many advantages for some time now. Her center offers a programme that focuses on training participants and helping them foster the right set of skills in order to become effective data professionals.
Her work has helped her gain tremendous insight into the promising (and often mysterious) world of data.
The origins of data science
According to Sharala, the smartphone is the key invention that ushered in this transition towards an awareness of data science and Business Intelligence.
“When that kind of computational power is in your hands, that leaves a huge footprint on the internet.”
Everything you do on the internet (anything you post, upload, write or publish) is put up online as data and, over the years, that has grown exponentially. When there’s such a huge amount of data, we’re able to work with more information than we had even just a few years before.
You can start to look at behavioural patterns. You can identify what each individual is thinking about and you can start predicting how the market might change.
Naturally, a huge amount of data requires efficient technology for data storage purposes. Data formats, in turn, began to grow from a simple handful to a complex range. New technologies were created to collect, store and process data in vast amounts.
The programming languages, methods, tactics, skillsets as well as other abilities used to handle this data have come to constitute a science in its own right. Data science is an old analytical approach that has been refashioned and brought up to speed for today’s world.
Key skills
Before prospects embark on a journey into the promising field of data science, Sharala notes that a certain set of hard skills and soft skills (or smart skills as she puts it) will be integral for long-term career progression.
Hard skills included mathematics and statistics as the base for more technical pursuits.
“Another really important part would be programming skills. That’s why coding schools and computer science schools are very important.”
Maths, science and computer programming early on (with mathematics being a priority) can go a long way and help career hopefuls gain a better understanding of machines.
Essential ‘smart skills’ include; critical thinking, problem-solving, collaboration, the ability to be able to tell stories and creativity.
Being agile with regards to communication is also something that Sharala talks about very often, particularly around Asia.
Capitalise on opportunities for communication and learn to present your ideas with precision. It’s a skill that machines don’t really have and it is a major part of conveying information derived from the cryptic processes of data science. Be the human face, a bridge between machines and humanity.
A race towards data-driven organisations
As Big Data and analytics continue to be pushed to the forefront, companies become transformed and seek to improve their data-driven capabilities. Sharala says that businesses should first of all start looking at how to support data-driven strategies and that the process needs to be top-down, starting from the board level or management level.
“There’s no one reason to adopt data science and analytics but the main reason is to stay relevant.”
Disruption is imminent across all sectors and many businesses aren’t going to be the same. So many organisations struggle to remain relevant and this is where data scientists can fit in.
“Analytics will give you the edge and the advantage, and even change your model totally.” She says.
Talent is key
In countries like Malaysia, the biggest struggle is the shortage of talent. Businesses can’t change and keep their offerings relevant because they cannot find the right talent to implement data-driven processes.
“Organisations are finding it equally challenging to find skilled data scientists so they also have difficulty in understanding what it means,” Sharala adds.
“They have these unrealistic expectations on data scientists, so I think it’s very important that the business understands what kind of data scientist professionals they need.”
Sharala also emphasised on the need for fresh graduates to gain employment in the field of data science instead of industries relying only on experienced veterans.
The introduction of new data science talent can benefit both fresh grads and the industries they operate in. Fresh grads can be more creative, more experimental and more open to versatility, traits that are sorely needed in today’s fastmoving world.
It’s official. The future of work will most probably include increased demand for skilled data scientists and, as Big Data continues to get ‘bigger’, expect big capabilities and even bigger opportunities. An influx of promising new talent can be a crucial part of keeping up with the advances that are underway.
