4 min • 17 March, 2020
Until now, the difference between an expert and a citizen has been simple: education and cost.
Could a business with no personnel versed in data science and analytics, nor the budget to obtain the tools needed to make heads and tails of its data, match an enterprise with the correct ingredients stride for stride? Probably not. But that, like everything else, is changing.
The way we communicate has evolved significantly over the last thirty years, and, along with that, our understanding of the world. It has fundamentally changed the way we do business and access knowledge, now that we have everything we could ever need at our fingertips. Today, every single one of us can be an expert. We no longer need to consult a conventional specialist to solve societal or business problems – with the correct no-code tools citizens can too.
Citizen experts are the new paradigm, and the tools needed to bridge gaps in expertise are becoming more prevalent in the modern workplace, enabling and augmenting the workforce.
It’s easy to speculate on the future of data science and analytics, but the truth is we just don’t know how it will take shape. However, what we can do is look at present-day challenges, and start to address the widening data science and analytics skills gap.
Companies using data-driven decision making are, on average, 6% more profitable than their competitors.
As data firmly cements its reputation as the modern business currency, more emphasis has been placed on collecting and analyzing that data. The race to become more data-driven has led to an increasing need for people to fill those roles, so it’s unfortunate then that a lack of funding, time and support for training have made data science a challenging entity to embrace, despite research showing that companies using data-driven decision making are, on average, 6% more profitable than their competitors.
Some have gone so far as to call it a sector in crisis. An abundance of data, but a severe lack of talent able to take that data and turn out insight. According to IBM’s The Quant Crunch report, “machine learning, big data and data science skills are the most challenging to recruit for, and can potentially create the greatest disruption if not filled.” The growing demand for data science and analytics workers puts pressure on the supply lines, which are, at present, lagging.
Could this shortfall in talent bring those gains from data science and analytics to an eventual stop? Is it truly a sector in crisis, or are there ways and means to bridge the skills gap?
Here at Gyana, we’ve created a platform that bridges the talent gap. VAYU is a no-code platform that empowers virtually anyone to become a data scientist. With VAYU, anyone can create a framework of understanding, distill data, give it a narrative, and visualize it. We’ve stripped away the barriers to data science, leaving you with a tool that can augment your existing workforce, whether they’re data-savvy or not.
VAYU was created with the sole purpose of democratizing big data. Why does it have to be reserved for experts? We knew there was a way to address this modern business challenge, so we did.
There are currently children in schools whose future jobs might not even exist yet. A light has been cast upon the potential ramifications of such a situation. With that being the case, educational institutions need to become more agile and responsive to workforce needs ahead of time. Collectively we must steal a march on this outcome by using what we have at our disposal.
Tech-heavy workplaces allow little time for training. Finances can also be a constraint. No-code platforms like VAYU ease the burden by empowering individuals, which in turn benefits businesses to no end.
If you want to find out how your business can benefit from VAYU, or you want to become a citizen data scientist, subscribe to product and company updates here.