We’ve had our share of predictions in possibly every field that one can think of. Data analytics is one field that is never behind when it comes to predictions. With an enormous amount of data to deal with, this field opens doors for truck-loads of predictions and it is for this very reason that “analytics” has been the centre of attraction in probably every aspect and garnered eyeballs from all across the world. Some of the key predictions for this field in the years to come are-
Data privacy
Data privacy/security has always been a concern. With exponential increase seen in the amount of data all across the world, securing it has become even more crucial. With this, it is likely that companies will now realize that data privacy and governance is not something that can be achieved with separate standalone tools. Hence implementing this as an integral part of the analytics infrastructure to serve the purpose will most likely be given importance like never before.
Data scientists
All this while, we have seen data scientists being involved in tasks pertaining to the pre-production development stage. They’ve been handling raw data and simplified it to the extent that on being passed to the next stage, the code translators are in a position to draw the best possible conclusions. But, in the years ahead, it is predicted that there’s so much more than the data scientists will be entitled to do. They themselves will be capable of handling enormous data all by themselves (way beyond the pre-production stage) thereby reducing the number of code translators required. Also, the code translators who’ll be involved have an advantage of not dealing with too much work.
Emotional analytics
For a business to flourish, customers play a pivotal role, without any doubt. Simply put, they are no less than a treasure for the business. Understanding customer behaviour thus aids in achieving better results as that helps in functioning as per their needs and demands. In the coming years, it is very much likely that the businesses start prioritizing ‘’emotional analytics” like never before. This would require predictive models and Artificial Intelligence/ Machine learning to analyse the choice of words, voice tones, facial expressions and a lot more to understand the human behaviour thus paving way for tailored products and services as per the customer profile.
Machine learning
Needless to say, machine learning has seen a wide range of applications. So much so that there’s hardly any sector that hasn’t seen machine learning being put into practicality. However, what has been observed over the years is that heavy importance was been given to building own machine learning platforms. But, the future is likely to show us a different picture altogether. It is very much a possible scenario wherein on recognizing where the core competencies lie, we’ll see enterprise backing out from coming up with their own machine learning platforms. Maybe now is the time that they realize ‘more value is obtained by applying Machine Learning to business problems’ rather than investing resources (time, money, etc.) in building and maintaining the tools all by themselves.
Cost-cutting
2020 has shaken the world to the extent that it might take several years for the world to recover. With that being said, every firm will now look for options that’d cut down the expenses in the coming years. As far as analytics is concerned, it is very much possible that firms will consider partnering with the ones who are already established as they wouldn’t want to get into any kind of risk by partnering with new/emerging firms.
There is no limit to how many predictions about anything can be made. Same is the case with analytics. With literally tons of predictions about analytics already in line, it is not all surprising to keep adding to the list for the sole reason this field doesn’t choose to get old!
