As a disruptive trend, cognitive analytics is that which enhances the human decision-making process as a result of using ‘heavy’ data such as that gained from cloud computing or the knowledge that is shared in a community or group of people. It assists us to make conclusions around a specific area and to provide support for a more improved decision-making process.
While there are some relationships with business intelligence, especially when it comes to using raw data, cognitive analysis deals with long-time historical and very big data. It is simply much broader in scope than what business intelligence has to offer.
This concept is new when compared to other ICT initiatives. But with more discussions happening around cloud computing and open data, especially in the public sector, cognitive analytics is starting to gain momentum. It is especially important as it can provide direct assistance on maximising the technology usage of the cloud and other innovations. Developing countries might still be a bit slow in adopting it as it is a new concept but it is definitely not too late to work in this area.
Governments should be using this as it relates to step-by-step prototyping. But it can only be effective when cognitive analytics professionals are involved in very specific areas. To this end, it will be useful for the public sector to partner with those companies in the private sector who have already developed solutions around this. This will result in government getting qualified people in the area so raw and fundamental data and processes can be organised accordingly to benefit from cognitive analytics.
The benefits of this are numerous. By being able to make considered decisions using historical data in a more precise and accurate way will provide significant assistance when it comes time to decide on specific concepts that require open data. When any data analysis takes place, it is more difficult if a single person is responsible for it. So a collective effort is required especially around natural language processing, structured and unstructured data, and in generating ideas that are more exact. Cognitive analytics means that it is all up to the person to use the information and start implementing it.
It is only a matter of time before cognitive analytics permeate every effort from business and government. People have specific demands and want real-time decisions to be made. For example, only a decade ago it could take up to a year to complete a government department roll-out. Today the expectations have changed and it needs to be done within a few weeks. So it is clear that in order to do this, you need to be in a position to make decisions fast hence the importance of cognitive analytics.
And as with any other technology, whoever started earlier when adopting cognitive analytics has got the first-mover advantage. This is also not a single component but requires historical data, big data, and other resources to teach the system accordingly. This year is definitely going to be one to watch when it comes to implementing cognitive analytics systems and those in the government and private sector best be ready to embrace it.