Bridge the ever-widening skill divide, dive into data
Amid all the conversations around economic slowdown, automation, Covid-19, unemployment, underemployment, un-employability and such like, one thing is becoming increasingly clearer – the world is witnessing another decisive division – the Great Skills Divide. There have always been these mutterings that colleges don’t teach the skills required by the industry – and that graduates are not ‘employable’ (interestingly, the biggest grumblers are people who are themselves products of the same education system and are doing fabulously well). I suspect these voices will grow louder as it’s difficult for trainers and learners to run with the sheer speed at which technology, and therefore skill requirements, is changing as we accelerate the digitalisation process. While this sounds like a big challenge, it also offers a great opportunity to those of us who are willing to make an effort to cross over to the other side of the divide.
We are in the midst of a Digital Revolution – driven at the core by high-speed internet connectivity and accelerated by the proliferation of mobile devices. We use this device to run our lives for us – from socialising and learning to ordering food and transferring funds. And not to mention watching movies, paying our bills and so on.
Driving this transformation is a web of complex technologies that make a significant, tangible and positive difference to the quality of our lives by making things more convenient.
One of the fall-outs of ‘digital’ is that we are generating data in unimagined volumes and at unimagined speeds. Every digital transaction leaves a data footprint. You also leave pieces of evidence of your behaviour online, which is of critical value to businesses who want to sell a variety of products and services to you.
At its simplest, therefore, digital is about data and technology, including the technology you need to get the best out of data. As a logical consequence, therefore, skills around technology and data are, and will continue to be, sought after.
The availability of huge volumes of data combined with our ability to access, store, analyse this data to understand our environment and business better, has made data the most valued resource today. This is also why I firmly believe that if you make data your career – that is, if you create expertise around handling and/or analysing data, you have a bright, sustainable career ahead of you.
To understand the world of data, we need to answer the following questions:
What is data? What is Big Data?
Data are characteristics or information, usually numerical, that are collected through observation. Big Data refers to such large volumes of data that are too large or complex to be dealt with by traditional data-processing methods.
Where is this data generated?
Data are generated from primarily three sources — social (posts, likes, shares, tweets, video uploads, chat etc.); machine (industrial equipment, sensors, weblogs; Internet of things – IoT – is driving huge volumes of volumes of data); transactional (company data like invoices, orders, receipts, inventory).
What are the different varieties of data?
Structured (transactional), semi-structured (machine) and unstructured (social).
Why are these insights precious to people, businesses and governments?
When we combine data from different sources and analyse it, we discover patterns that help us understand the present and predict the future. This helps us make better decisions that help us save costs, increase revenues and mitigate risks, while serving our customers faster and better.
This is a new breed of people who are proficient at working in some area(s) of the rapidly expanding data universe. My objective of writing this article is to introduce you to this universe and nudge you to consider a career aligned with data with some seriousness. Let us look at three broad career options with data at their core:
Data engineers execute the data strategy of the organisation which means creating the infrastructure and processes for identifying, storing, provisioning, processing and governing the data assets. On a side note, Data Engineering was the fastest-growing job role in 2019, growing by 50 per cent (Dice 2020 Tech Report) and 41 per cent of all data engineering work is done out of India.
Cybersecurity experts monitor, detect, investigate, analyse, and respond to security events to protect systems and data from cyber risks, threats, and vulnerabilities. According to IBM,India needs 3 million cybersecurity professionals and Cyber-Security Ventures says there will be 3.5 million unfilled cyber security jobs in India by 2021.
Data scientists use scientific methods, statistics, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured. The data science role grew by 32 per cent in 2019 (Dice 2020 Tech Report) and note that 70 per cent of all data science work is done out of India.
Reskill or regret – that’s the mantra for the times we live in today. But how does one go about it? The three disciplines discussed above require an understanding of fairly complex concepts as well as practice of applying these concepts and working with data and computer systems. I would therefore advise career seekers to get themselves adequately trained
before approaching the recruiting community. You have options of part-time (online, hybrid, in-class) and full-time in-class programmes.
I am partial to a campus-based immersive learning experience which comes with the advantages of a structured curriculum that includes experiential learning tools like labs and projects, the learning from intensive engagement with mentors, faculty and peers, the opportunity to network with peers and the alumni and, in several cases, the services of a structured campus placement programme. However, if you do not have the option of either giving up your current job or investing in a full-time programme, you could look at the other options.
Charanpreet Singh is founder and director, Praxis Business School Foundation