Data is exploding, and the science required to collect, analyze and store this data in a secure manner is also evolving at an unimaginable pace. The latest reports on data management trends and security strategies state that close to 100 zettabytes of data will be transacted globally in 2022. This volume of data will add to the data lakes that are already available in the form of historic data and predictive analytics. So, it’s good to have large data lakes, but do we have enough workforce to handle this? Business leaders say, not yet. According to the latest hiring reports specifically discussing data science roles, 90% of the vacancies in the organizations go unfulfilled due to a lack of quality talent. But, on the other hand, data analysts passing out with certifications are increasing in numbers each month. This is around 10-15 percent growth every quarter in data science analysts and certified data engineers. So, why is this an abnormal job fulfillment problem?
Let’s try and understand the problem by identifying current challenges in data challenges in data science and how some of the best data science training institute in Bangalore is helping solve these problems.
Problem 1: Looking at a data through a kaleidoscope, not a telescope
If you know the difference between a telescope and a kaleidoscope, you will understand what we are trying to say here.
People love data because it gives a variety of results… but the real business it is going to fetch is from the predictive intelligence, and not colored analytics painted in hues liked by analysts. Though business analysts have the power to sway the results of data analysis by deploying a biased AI algorithm, the picture will get murky if decision makers are unable to make a sense of all the data science has gone into during analytics. In short, good businesses use data to build colorful (often not so useful) analytics, rejecting the idea of having to find a landing ground for predictive intelligence.
Best data science courses understand this challenge. Therefore, the trainers are able to provide ample case study materials on how to create a very strong data science project for predictive analytics.
Problem 2: Data Science is yet to become a specialization in Engineering!
Data science is seldom taught in engineering colleges. However, the basics of data science such as Mathematics, Statistics, and Computer programming are focus areas in most engineering specializations, particularly in the first two years of the curriculum. In most parts of the world, data science is still treated as an area of research, and not as a full fledged area of specialization that can be included as a full time course in contemporary Engineering or Management classes. In recent months, there has been a shift from this conventional approach, resulting in many top tier colleges partnering with the data science training institutes in Bangalore, Delhi NCR, etc for domain expertise and workshops in AI, Machine learning, and data analysis. In some years, we might see data science become a core part of engineering and management students with the superlative assistance from the best AI ML and data science certification courses in Bangalore.
Problem 3: Job crunch
Professionals with a certification from the data science courses find a job within 6 months of completion. In most cases, professionals with experience get promoted to a higher designation with better salaries or are shifted to another team where there is a large scope of business development based on AI Machine learning and data science applications.
Moreover, many AI analysts and engineers are forced to work with projects that may not be good for the society due to a lack of awareness. For instance, dark web, ransomware, etc. Best data science courses educate students against joining such companies that indulge in evil applications.
For instance, data analysts with no graduation degree or a basic gradation from B.Sc. college might take up a data science training course to change their career roadmap. Within 6-8 months, with high quality training and learning experience in an experiential mode, these analysts get a job in relevant data analysis teams such as Marketing Analytics, Web Development Analytics, Web Scraping, data management, business intelligence, and so on. These provide opportunities to professionals and students willing to take the extra burden of learning something new in data science. Therefore, top data science courses help solve the problem of joblessness and non-employability by securing good opportunities in the best paying domains and industries in the world.