Introduction
In this technological era, there is always loads and loads of data being produced which basically uses lots of disk spaces, and it doesn’t necessarily have to be a technically giant company to have these amounts of data to store. These loads of accumulated data can simply be called Big data. So what good is big data if it can’t be used and is simply there to store, and there arises the idea of Data science where you could just use the huge amounts of data to improve the statistics or simply put together a business strategy to be a successful leader in the current market. So primarily, data science could mean as simple as analysis of the big data; but it also has a big role to play in all the other buzzwords hanging around in the market right now such as Machine learning, Data analysis, Data visualization etc. Data Science is one of the top trending technology of the era and data science has stretched its roots deep down in the corporate industry. Due to this vast inference, new age learners and working professionals are keen to learn this technology. To curb this, various data science training courses are available through which one can master data science and begin career as a data scientist.
Why Data Science?
The main reason data science has been a buzzword since 2010 is that it is essential for ‘Prediction’ i.e. a lot of mathematics and statistics come into play when you want a particular algorithm to give you a better prediction which is directly proportional to the success a company or an individual in the trending market situation. Even if you consider the role of data science in machine learning, the basic operation of machine learning algorithms is to work on the present data set at hand and act or operate accordingly by choosing the best path. And as mentioned it uses a data set which is to be presented there depending upon the work happening there so appropriate samples at appropriate times and places, and this doesn’t happen magically it is done by using data science. So similarly, whenever and wherever there is the need for data there is the presence of data science and therefore it has been a buzzword for so long and is not going anywhere.
What does it take to be a Data scientist?
By now one would be pretty clear that being a data scientist includes being good at statistics, math and more importantly machine learning, artificial intelligence as they will be dealing with data sets there, data visualization which is primarily used to get the insights into the business model and help the company improve their performance and also different data cleaning processes because one cannot simply understand the raw data that is present out there as well as we should also provide appropriate data to the algorithms in order for them to provide correct predictions.
As there are many companies willing to work with big data, every company needs a data scientist as he helps the company grow as well as help the company’s long-term survival.
Therefore, aspiring to be a Data scientist is not a bad thought especially at this moment as there is an increasingly high demand for them in the market and every company as well. And it will be a buzzword as long as the data is there.