Chandler Bing’s job in the 90s was ‘Statistical Analysis and Data Reconfiguration’, a seemingly boring corporate job (hoping somebody got the F.R.I.E.N.D.S reference!) that he got ragged for regularly. Now fast forward a few years and we have jobs like Data Analysis and Data Science (fancier versions of Mr. Bing’s job of course) taking the world by storm, and in fact being touted as the Sexiest job of the 21st Century and Top high paying jobs.
So how did this job go from geek to Greek god status? For one, our perception of what data is and what we can do with it has seen a monumental shift. Data analysis and processing was just a part of a business, among many other fictional units. The expansion of the internet and growth of internet companies has given businesses access to data which they did not even know existed. With the exponential increase in computing power and capabilities, we’ve learnt how to make this data work for us and guide us in making decisions for the future based on historical data. For lack of a better phrase, data analysis opened our eyes to a plethora of possibilities that have changed the way organizations function.
Companies of all sizes are scrambling to find suitable talent who can help them put their data to better use. This has created a niche market demand for professionals with analytics and data handling skills. In fact, reports have stated that there is a gap of approximately 2,00,000 job roles to the available talent. The demand is huge and opportunities are many. As the saying goes, strike while the iron is hot.
Dealing with data is not restricted to the technical or internet realm. All domains use data at one level or the other. The predominant ones right now would be BFSI, retail, supply chain, sports, healthcare, manufacturing, research, governance while we see increased adoption in the fields of media, agriculture, travel, energy among others. The demand is not just for people with pure analytics skills, but also for people who can leverage their domain expertise with analytics.
So, you see, analytics is a skillset that can not only survive on its own, but also augment well with other skills to produce a professional who is multitalented and can set business context to the data.
With automation on the horizon and replacing the current set of jobs, we have to develop new competencies to stay relevant. One thing we know for sure is that data skills are always going to be valued (at least that’s what the data tells us).
The future is data driven, are you?