The Future of Data Scienct

Data Science is the new ‘hot job’ and suddenly everyone wants a data scientist because of their ability to not only discover patters, correlations and causation, but also to analyze them and find those ‘lurking variables’ which can be optimized and ultimately affect the balance sheet. However, till when will this last? It may be a little early to address this question, however it is not a wrong question, as all new methods, technologies follow a hype cycle and so will data science wherein, sometimes its growth will reach a plateau from the exponential curve it presently is following.

As per The Gartner Top 10 Technology Trends for 2020, automation of data science tasks will enable data scientists to carry out high volume of data analysis – something which is presently being done by specialized data scientists. Also, as per Gartner, by 2025 scarcity of data scientists will no longer be a hindrance for organizations. This means two things, firstly, some tasks of data analytics will be automated – which is understandable given the advances in machine learning and deep leaning taking place. Secondly, it also means that machine leaning models will be able to undertake more independent and analytic tasks than they can do so now.

This, however, should not be considered bad news, as, this is the normal curve of any technology/methodology – it takes up some human jobs and creates a different set of jobs which are more technical. The same will happen with the machine learning models being trained now, they will lead to a set of tools being created which will make slicing and dicing data simpler and automated and In doing so, they will lead us to new intellectual frontiers, which will define the trend as we enter the third decade of the 21 century.

My Random Thoughts