Data literacy is fast becoming as important as writing or math. It has been compared to gold, oil and other precious resources of the world. Today, data skills are essential not only for engineers and researchers, but also business workers, entrepreneurs and, increasingly, creative professionals. However, working with data can be challenging even for technical specialists, let alone for people from other backgrounds. So where does that leave us?
Before you jump to the conclusion that data is not for you, perhaps you can draw some inspiration from my experience of learning and later teaching this important skill set.

Speaking the Language of Data
I immersed myself in the early Web when dial-up Internet was introduced. Among other interests, the Internet sparked my passion for learning new languages and connecting with people around the world. Subsequently, working in different countries further spurred my determination to pick up local languages and use them to share the amazing world of technology with my friends.

Fast forward to several years ago, I joined the tech industry. As it happens, the years I spent in the industry were characterised by the emergence of Big Data. One day, a colleague who worked in analytics introduced me to SQL. I recall staring at a barrage of symbols and commands, and imagining not ever producing anything similar.

Then, I started dabbling with this mysterious “Sequel”, and an unlikely analogy crystallised. Like every language I learnt – be it English, Spanish or German, each has its distinct grammar and vocabulary. And as long as these two pillars are mastered, the road to fluency becomes open. Similarly, I realised that SQL commands are in fact a tongue in its own right with its unique grammar and vocabulary.

Sharing about Learning the Data Language
This realisation turned a previously technical subject into something close to every human being – speaking languages. It helped me to learn SQL as well as relate to people who struggle to grasp it. So now, whenever someone asks me to explain SQL, I would approach it as if we were learning to converse in a new language – ask a question, get a reply, make a statement and so on.

And when people struggling with this technical subject can finally “have a chat” about it, I would feel really proud. It also heartens me to know that a training course which I created and deployed using this approach for my organisation stays relevant even after several years.

Hence from my experience, it shows that even the most technical subjects share parallels with concepts naturally intuitive to people – such as languages. Simply by applying such analogies, learning data skills can become a lot more accessible for everyone.

First published in the IT Society Magazine by the Singapore Computer Society