It is a widely known truth that the presence of an inexplicable amount of data around is shaping our lives and it surely is molding the way business is done. Big Data has open countless avenues for businesses to upgrade the ways in which they function and gain higher profits. Big Data is their golden ticket into a lucrative world where they can cater to their clients in a much better manner.
Hence, the demand for people who understand data is unimaginably enormous. Companies are chasing data scientist as well as analysts who can support them in their journey of optimizing data in the best fashion and attract immense profits. If you wish to be a part of this which is kind of an obvious decision to make for any tech professional who is ambitious, read on and understand what will it take for you to enter this industry.
The Growing Demand for Data Science Professionals
For making a career in data analysis, it is essential for you to be well-versed in some of the most popular programming languages like python. Though learning R is not a bad option but in this article, I am going to focus on how advancing in the Python language can be beneficial for an aspiring data analyst.
I would not give you any false hope by saying that it is easy to learn python and anybody can do it. To tell the truth, it does take time to gain expertise in this language but if you are willing to work hard and already have some experience in the technical area, it would not be a very tough nut to crack. Once you make an effort to master python, you will definitely get your due since there is a huge demand for people with competence in python in the job market. I have data to prove that. There will be a 28% hike in the requirement for data science professionals by the years 2020, as reported by IBM.
There is a wide range of sectors you can make your niche after gaining knowledge in python. From medical research to machine learning to automotive, every big industry is welcoming data science professionals with the capacity to use famous programming languages. Perhaps you must be a little intimated of joining the data science zone since it sounds serious and it may feel that you might have to cross multiple hurdles to reach your destination of becoming a successful data scientist, if you maintain your cool and keep walking on the right path, you will certainly get there. As they say, hard work always pays off.
But, why python and why not some other programming language?
The reason why I am pressing on the importance of python is that it a highly flexible language and is used by a majority of people in the data science areas to fulfill a multitude of purposes. And also because it is easier to learn as compared to other languages.