This is a post about negating some widespread notions about data science and establishing the value above quantity. If you are planning a data science certification in near future, this could be very important for you.
The Harvard Business Review used the phrase ‘the sexiest job’ to refer to data scientists back in 2012. A lot has changed since then. The discipline has evolved over the years with an increasing focus on artificial intelligence. But it has never really shaken that lucrative tag off.
Aspirants across the globe have flocked to universities, training facilities, and online classes to start a career in data science. And why should they not? A data scientist job offers unmatched pay packages and a glorious career in one of the most advanced fields of technology. But does everyone working in the field enjoy their work? I doubt that.
The hype, the misdirection, and the reality
50% of the data scientists were looking for a different role in 2020 and it had nothing to do with the fear of layoffs following the pandemic.
29% of these respondents cited poor leadership as the reason for their dissatisfaction with their roles while an equal portion identified the lack of workable tools and infrastructure as the reason.
The hype built around data science has done two things. One, it has attracted a large number of aspirants who had not the slightest idea about the field, and two, it has lured businessmen to invest in a technology they had neither the vision nor the infrastructure to utilize. The result, of course, is widespread dissatisfaction and loss of faith.
It all boils down to enjoying what you do
We have all made impulsive decisions. Sometimes they work and at other times they do not. It is pretty easy to lean towards a career in data science and spend a fair amount of time and money learning a skill you do not find interesting.
Job satisfaction comes pretty low on the list of priorities for most of us, whereas it should be right on the top. There are different aspects of data science that are suitable for different people. Matching the people with the roles ensures productivity, growth, happiness, and reduces attrition.
So, ask yourself, what is it that you like to do? Is there a data science role that fits you? Enroll for a data science certification only after you have found answers to these questions.
The different roles you can look into
Data science is an umbrella term covering multiple roles. Each of these roles demand different skill sets or different variations of the same. We will go over three roles related to the field of data science and understand what role they play in the real life scenario.
Handling the volume, velocity, and variety that comes with big data is a difficult task and it requires robust infrastructure, and detailed security measures. A data engineer is responsible for building this infrastructure. They ensure that data is easily accessible by the data stewards and analysts.
Data engineering is a code heavy job. It requires excellent competency in a query language. If you want to be a part of the data science fraternity and code extensively, this is the right place for you.
The data analyst looks for patterns in data and derives insights from the data. Another large part of the analyst’s job is to connect business to data. They understand business problems and interpret them as data problems. Then they analyze data to find out how the data correlates to a certain business situation.
Data analysis is essentially a creative job. It involves finding ways to connect data to business and then presenting a story to the stakeholders.
Data analysts need minor programming skills, especially query languages. Data visualization skills are critical to their job. They also need a strong knowledge of the business domain.
Data scientists ideate machine learning models to make data driven predictions and prescriptions. They need a very strong grasp over statistical concepts. This job needs a lot of practice and extensive studies. Data scientists are often people with doctoral or postdoctoral degrees, but that is by no means an essential criterion.
No data science certification can prepare you for the role of a data scientist but a good course can initiate you in the right direction.
No matter what path you choose, always remember that in the long run you will succeed only in what you enjoy doing.