Today, it is practically impossible to imagine a life without data. Travel, tourism, education, healthcare, robotics, you name it and the realization that all fields rely on data, hits you hard. The extent to which data is generated on a daily basis is way higher than what one can imagine. Evidently, businesses have become increasingly reliant on data in order to make better decisions and improve customer experiences, in order to gain a competitive advantage over market players. Thus, having highly skilled data scientists in place is the need of the hour. Despite data science being the most sought-after career path and rising demand for data scientists across the globe, it turns out that these expectations are not met. Simply put, the number of skilled data scientists with decent knowledge pertaining to data and data science is very less. It is time that we address the reasons behind the same and works to get the issues resolved. Have a look at some of the major problems, which when handled now, might lead to a better tomorrow.
There is a clear lack of group learning as the current online training methods offer limited peer-to-peer or community engagements. Since group learning is missing; the onus to obtain optimal learning falls on the student itself. Evidently, one loses motivation.
Yes, the demand for data scientists is exponentially increasing with every passing day. However, the number of skilled professionals in the field of data science does not match the growing demand. This poses a problem at the time of recruitment as well as the hiring managers have to look for fairly skilled aspirants who are lost among a crowd holding just certifications. This further implies a lot of time as well as money is being spent to hire skilled data scientists as compared to hiring professionals for other roles. Efforts must, therefore, be taken to upskill the individuals so that finding the right individual for data science wouldn't be a cumbersome task.
One of the major reasons why we aren't able to find fairly skilled data science professionals is because personalized and outcome-oriented data science training turns out to be affordable to the extremely low percentage of the eligible population. Now, whether the training cost needs to be cut down or no is something that we really need to address.
Curriculum update
No wonder the industry requirements are changing rapidly. However, a point of concern is that the colleges and universities are not that equipped to handle the same. This turns out to be the reason why data scientists who pass out every year are not up to the mark. Constantly updating the curriculum is the need of the hour.
Team collaboration is that one skill that a good data scientist should have. This is because they work closely with business, product, and engineering teams. On the same lines, networking is equally important. The reason being – interacting with other data science professionals makes them understand the current use-cases of data science in the industry. Such a type of learning is only possible in a closed-knit, cooperative community of aspirants as well as professionals.
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