Big Data and Machine Learning are the two buzz words in the industry today. The way companies in various sectors are adopting data science approach to improve their top line and bottom line numbers has been phenomenal.
With the huge popularity that the data science has achieved in the recent past, it’s high time to take a step back and understand how different organizations fared when they employed ML or Advanced techniques to improve their business operations. Towards the later half of 2015, there was an article published by Gartner where they showed the hype cycle of the emerging technologies.
http://www.gartner.com/newsroom/id/3114217
What is interesting over here is to find that “Machine Learning” falls in the “Peak of Inflated Expectations” in the Hype Cycle which shows that there have been successes (often owing to the initial publicity) accompanied by scores of failures. This may look scary at first since Big Data and Advanced Analytics are supposed to lift up the business. We definitely wanted this to be in the “Plateau of Productivity” on the Hype Cycle. Technologies falling in this plateau region are the ones that are adopted by all the mainstream businesses and have positive ROI. It’s promising to see that both “Machine Learning” and “Advanced Analytics” are expected to reach the plateau in 2-5 years’ time.
Gartner’s Hype Cycle shows that benefits of Machine Learning and Advanced Analytics have not yet reached its true potential. This also shows that it is the best time to be in the space. As shown through the article, the companies who can adopt these technologies in this time and space will get the benefits of it within the next five years.