By Dr. Indradeep Ghosh, Associate Professor & Dean (Faculty), Meghnad Desai Academy of Economics (MDAE)
Data is the new oil and the world is in urgent need of people who can extract the most valuable information from this humongous amount of resource, expanding rapidly every day. According to computer giant IBM, 2.5 quintillion bytes of data is being created every day at our current pace. Although even this figure is big by any standard, this pace of growth is set to increase staggeringly as technologies such as the Internet of Things assume more significant roles in the future.
Availability of data in disrupting domains
The figures describing how much data we are stockpiling every day can be extremely overwhelming, to say the least. The availability of massive amounts of data has completely transformed the domains of planning, forecasting, execution, monitoring or even human interaction. No business, government or individual today can ensure the survival of their institution without incorporating data analytics into their operations, and that too at a significant scale.
However, the supply of skilled data analytics talent still does not match the demand. According to IBM, the annual demand for data scientists, data developers and data engineers will lead to 700,000 new recruitments by 2020, making them the most sought-after profiles over the next five years! This also means that those who acquire the skills will be able to command a substantial wage premium! The average yearly salary of a data analyst is among the very highest, with figures ranging from €30,000 to €50,000 for junior profiles, through to €99,000 for senior ones.
Numbers are not all prospective analysts in essential
It is important to keep in mind that just being able to crunch numbers will not get you to the top of the corporate totem pole. It is equally important for prospective analysts to develop the ability to explain the correlations obtained from the data through theoretical mechanisms. Essentially, this causal story-telling is what will help senior management take policy decisions, and the ability to analyse and interpret data comes only through proper training in domains that give enough scope for such data-driven analysis.
Economics then serves as a great missing link to equip potential data analysts to strengthen their interpretation game as the subject deals in terms of causal narratives driven by a model-based understanding of the world. However, it is different, and somewhat more complex than research conducted by, for instance, a physicist or a chemist, as the fundamental material of analysis is human behaviour, which is not inert. Data, being the outcome of, and the determinant for, human activity, is extremely chaotic in nature, and it requires higher order thinking skills to identify patterns and make sense out of the madness.
The solution is a combination of data and economics
The combination of data analytics and economics training ideally equips the prospective professional of tomorrow to help institutions and governments determine the future course of action by interpreting available information in the most logical way possible. The two subjects, essentially train a student to ask the right questions given a set of information, the correct answers to which can then be formulated through a proper combination of quantitative, analytical, programming skills to produce actionable insights.