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Big data is expected to rise exponentially from USD 28.65 Billion in 2016 to USD 66.79 Billion by 2021. The artificial intelligence market is expanding with companies making incredible strides to adopt the new technology into their existing system.
But, there are still specific uncertainties and questions alien to the technologist. With immense hype and expectations, companies are starting to develop more interaction between humans and machines to record and notice the changes that the technology is experiencing.
However, in the practical phase, data projects are working extensively toward improving insights and prediction to take better decision. Data science projects will improve with advanced data from non-traditional sources. It is a difficult job for an individual of a company to identify the problems related to the projects and act accordingly. As per records, nearly 80 percent of the data scientists working globally play a major role in the top most companies of the world.
However, the exponential growth in demand for data scientists around the world has led to companies not willing to make advancement in their computer learning initiatives making it hard for the scientists to cope up with it. Data scientists are finding new research techniques including the focus on data governance, MDM, compliance and so on, which are eventually becoming the main reasons for them to change their jobs.
At last, implementing a collaborative technique can make data work much efficiently when it is split accordingly among the data scientists. Also, splitting roles in the workplace helps in collaboration and workflow including improvement in the overall analysis of the project.