In today's world of fast-growing technology, acquiring the right data and managing that data accuracy is very important. Companies and businesses depend on data to run their operations and make decisions. There is a very lucrative career designed around data science, and students of data science must have the best data science certifications to bag such high-profile jobs.
Are you thinking of building a data science career in 2023? Then this article is a must-read for you as it talks about everything you need to know before jumping into the world of data science.
What is Data Science?
To understand the use of data science, we first need to realize why history is important. We need to study history in order to make sense of the past and therefore predict the future. Similarly, data science professionals take raw data and transform it into something that is understandable and meaningful to the business. Like history, data science has the ability to understand the past and provide recommendations for the future.
Thus, in layman's terms, a data scientist solves business problems using data. A data scientist is like Sherlock Holmes staring at pieces of evidence except there are millions of pieces of evidence and only with the right statistical framework or machine learning algorithm, the problem can be fixed.
Hindrance in Data Science
As popular data science is, it’s one major hindrance is an irony in itself. What complicates the exterior view of data science is that certified data scientists enter the world of data science through various paths and then develop some niche skills down the road. The 2022 State of Data Science report by Anaconda found that around 20% of students who want to make a career in data science exclaim that their biggest concern is the want of clarity around what experience is required for data science – even the job description in data science is not concrete. A person working in this sector will have to be in system administration, cloud engineering, data science engineering, or research.
There is not one mold for a data science program. One does not even have to be from a tech background to work in this field. There are also various types of data scientists such as generalists who work with machine learning models, forecasting, and statistics. There are also data scientists who specialize in certain things such as working closely with the production team and helping the business make decisions, experimental or concrete.
Misconceptions about Data Science
Three major misconceptions about data science can be observed in a data science career…
· Must be a Math Genius!
It has become a common notion that people have come to assume certified data scientists to be absolute geniuses with Master’s and Ph.D. (s) in mathematics. In reality, with the help of tools like Python and other data science packages, not everything needs to be calculated anymore. A clear understanding of the basics is more than enough for data science.
One does not need to be a math genius. In fact, among the millions of data scientists, it's highly improbable that all are excellent in mathematics. All one needs is the best data science certifications and the occasional help from Google or StackOverflow.
· Data Science is Magic
Data science may seem like magic because data science professionals can make predictions about the future of a business by examining the data. In reality, spending a lot of time with the data, studying the data, and eventually being one with the data will help to make such predictions. One should start working with something simple and then slowly build on top of the data to make the solutions work.
One thing to remember is sometimes the most uncomplicated and simple solution is the best solution of all. The best in the data science career are the ones whose foundations are absolutely clear and who can easily find a simple solution to a problem and not go after advanced jargon while not knowing anything in reality.
· Technical Problem-solving is the only way to Communicate
Data science is more than just technical skills. A certified data scientist must have people skills and must know how to communicate with soft skills such as empathy and understanding.
Data science professionals have to understand data and build models for such data to be easily interpreted but there's more to their job description than that. These people have to be in direct contact with the product managers of the business they are working in and must have empathy for the stakeholders because it is with the data science they are influencing the business and people's lives. They must educate these people and make them understand the data while making predictions.
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