Machine learning and Data Science are having a profound impact on the existing businesses, and are quickly turning into differentiations and may sometimes even become a case for survival. If you are quickly able to categorize the impacts that you may have potentially, into digestible categories, and be able to communicate the potential each category has, will help your analytics and data leaders in driving better results.
The innovation here refers to fostering of some new thinking and creating business disruptions that are based on the field of data science. With their innate capability of being able to frame the most complex of the business problems in to machine learning or into operations research problems, the data scientists really are the key people who can help us unveil better solution for our old problems. In doing so, it is also possible that they will even find newer problems and the approaches that were not previously known to us.
An Example from a game
One of the examples, that was made popular by the book and the film based on it Moneyball, went on to show how the old ways for evaluating performances in the game of baseball were largely outperformed when the concepts of data science were applied. One of the basketball teams used techniques from data science in overcoming their financial disadvantage. They achieved this goal by putting to use the concepts of analytics in identifying the players who were high-performing and other teams had just overlooked by the use of their traditional methods, and hence acquired the services of these players at a much lower cost. This resulted in a series of wins for them in the league over the teams who had spent a much larger amount of money in hiring their players
An Example from UPS
Another example where a similar thing happened is that of a multinational delivery company for packages, UPS. Its ORION (On Road Integration of Optimized Navigation) system put to use the theories of Data Science in figuring out how to dramatically change how their delivery trucks were routed by the use of many newer data sources. The impact of this was that hundreds of millions of dollars were saved and it also improved their customer service.
Exploration here refers to the exploration of unknown patterns of data that are transformative in nature. The people working in the areas of Data Science training in hyderabad should be given a free hand in order to undertake expeditions in big data where there is a lack of a clear objective. The only objective in such expeditions should be no other than just exploring the data in order to find some past undiscovered value.
For instance, the data scientists working at a provider of maritime services in Japan realized that while providing their classical services for the ship classification, what was being collected was If they could apply the right kind of analysis on this data, it would mean that the ship operators could get reductions in their equipment failures and their lifetime costs for maintenance by almost 10%. This helped them increase their market share while providing their customers with a value-added service.
If you would like to be part if this cool industry that data science is, you will need to put in some good work into studying the concepts which you can get from Data science training
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