We have been experiencing lots of discussions relating to machine learning and artificial intelligence for quite some time now, but do we really know what they hold for us in the future?
The concept of data science is not new to us. It has been in use for the past many decades, however, all the research regarding data science was theoretical or mathematical back then. As there was a lack of means to apply it in the market.
The change in data science that we see today is due to three factors which are:
- The availability of huge datasets which are worth working upon.
- Robust machine learning algorithms.
- High-tech computers to utilize those algorithms as well as evaluate huge data sets.
Able Data scientists who keep brushing up their knowledge by pursuing popular data science and big data analytics certifications are well aware of the developments taking place in this field and are witnessing some trends that are shaping data science differently.
Kirk Borne who is an Executive Advisor at Booz Allen Hamilton and famous Data Scientist emphasized that in today’s world of analytics, companies, and people should be inspired. He shared a few trends which he feels can frame data analytics’ future.
- Internet of Things:
It refers to a developed wireless network. The market for IoT is expected to expand from 170.57 billion dollars in 2017 to 561.04 billion dollars by the years 2022. And this has been possible due to the emergence of modern analytics along with data processing techniques. As now we can derive useful results out of large volumes of data that is accumulated from M2M communication devices.
These days the retail market has developed into a hyperactive one. Personalization has become an essential part of it as it increases someone’s chances of selling more products to consumers (by gathering information about the customers). The data that we have on our phones are constantly being analyzed to know our preferences for providing us the products or services the way we like it.
- Artificial Intelligence:
It is changing direction towards augmented intelligence. It targets an assistive role of AI and puts emphasis on the factor that it is created to upgrade human intelligence and not replace it.
An AI program is absolutely competent to make decisions after evaluating patterns in huge datasets, however, that decision completely depends on the data that human beings give to the programming to apply. The word augmented means to improve, so basically it strengthens the role played by humans in discovering relationships as well as solving problems by using machine learning together with deep learning algorithms.
- Machine Intelligence:
It involves the enhancement of computer systems that should be capable of performing tasks that usually demand human intelligence. It implies to the machines that are designed to follow a biological neural network approach.
Such machines can learn the arrangement of data flowing data, make anticipations and detect inconsistencies. They can plan their future work with the help of a roadmap that the brain gives owing to the biological approach.
- Behavioral Analytics:
It plays an essential role in applying traditional physiology in order to improve ways of marketing to people. It is considered to be an efficient tool for analyzing human behavior in some restrained environment. With the help of behavioral analytics along with personalized messaging, you can enable brands to convert normal users to super involved power users. It can be put to other users as well. For example, sensor data can be used to track patterns in traffic.
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