In a Nutshell, What is a Data Scientist?
There are so many concepts and terms associated with what a data scientist is, and I know that many people have no idea what it is. Well, you’re in luck today! I will explain to you in a nutshell what is a Data Scientist.
But before I start, I need to explain some concepts, because somehow you’ll find them on the internet.
- Big Data
- Data Analysis
- Machine Learning
- Data Mining
I know these words may sound frightening, but you will find them regularly, and you need to understand.
Big Data: When it comes to Big Data, it is almost always connected to an extraordinary amount of information stipulated to process. Moreover, it is often referred to as 3 V: Velocity, Variety, and Volume when this topic comes into the conversation.
Data Analysis: A method of collecting, analyzing, and converting raw data into helpful information for specific purposes.
Machine Learning: There are numerous fancy definitions out on the internet, but essentially, it is a tagger of things. Machine learning is a subdivision of Artificial Intelligence (AI) that makes computers learn from data.
Statistics: Essentially, it is a discipline of concluding relationships with your variables and populations. With statistics, you can obtain samples and learn from them to separate the signal from the noise.
Data Mining: When you discover insights from data. This allows you to search through your data and identify correlations, patterns, etc. And use that information for decision-making.
After reviewing those concepts, I can finally answer you.
- A Data Scientist deals with data, whether structured or not.
- A Data Scientist uses statistics, coding, mathematics, etc.
- A Data Scientist is everything about processing and storing data to get information.
- A Data Scientist analyzes, stores, and reports data correctly.
- A Data Scientist uses a scientific approach to better understand your data.
- A Data Scientist is like being a detective by observing the problem, creating the hypothesis, and updating your beliefs based on your prior and posterior knowledge.
In a nutshell, as I heard it on a podcast named Naked Data Science, a Data Scientist is a Pragmatic Scientific Problem Solver. (I highly recommend this podcast)
What I mentioned above is crucial, and it is vital to get the point. When you think like a detective, and you are a troubleshooter as a Data Scientist, you have to be very clear that every problem you face is not the same.
Asking the right questions will significantly improve your performance as a Data Scientist because you need to understand the problem well to get an overview.
When you think like a detective, you must be curious, and you must have a good grasp of your variables because it will give you a big picture of what you’re dealing with.
I know that particular problems are very well defined, but you will not always have a clear picture of the problem you want to solve. Not thinking like a detective will limit your time and the time of others, and that’s why you should always look further.
Data science is a vast multidisciplinary field that includes many subdivisions, such as data visualization, machine learning, and artificial intelligence.
Being a Data Scientist is about being curious, asking the right questions, acting as a problem-solving agent.
“Naked Data Science:” N.p, n.d. Web. 30 April. 2021 https://www.nds.show.