Why you should be studying Data Science or Data Analytics to be a Data Scientist?

3 minutes reading time (646 words)

[:en]Have you ever wondered what happens to the data you register on social media platforms such as Facebook and Instagram? Have you ever thought why certain post that you see on your feed is so relevant to you? Do you think all these are just random suggestions?

Well, to answer your question – Data is the key.
Social media platforms like Facebook and Instagram sells the data you have registered with them to businesses whom then uses it to make better informed business decisions and models. A simple action such as liking or sharing of a post are all data that Facebook is collecting from you! Next time you may want to think twice before you click on the “Like” button. 😊 Now, can you imagine how much data are being collected every day?

Data Analyst VS Data Scientist
You may have come across these two roles thinking they are the same or wondering what is the difference between both.

Though both work with data, a data analyst sifts through data and seek to identify trends. They analyse data to uncover hidden patterns, correlations and other insights. They create visual representations, such as charts and graphs to better showcase what the data reveals and conclude if any business decisions can be made based on these insights.

On the other hand, a data scientist role is similar to a data analyst but at a much-advanced level. A data scientist holds an advanced degree whom majority was a data analyst before. Like a data analyst, they interpret data with charts, graphs etc. but also tend to have coding and mathematical modelling expertise. They can do the work of a data analyst, but are also hands-on in machine learning, skilled with advanced programming, and can create new processes for data modelling.

Job Opportunities for a Data Scientist
Data science is arguably the hottest career of the 21st century. From businesses to non-profit organizations to government institutions, there is a seemingly-infinite amount of information that can be sorted, interpreted, and applied for a wide range of purposes. This also explains why Data Scientists are highly sought for today. It’s also no surprise that Data Scientists have also made it to the list for Singapore’s top jobs in demand for 2019 with one of the highest-paying job in IT.
How to become a Data Scientist?
Data scientists come from a wide range of educational backgrounds, but the majority of them will have technical schooling of some kind. Data science degrees include a wide range of computer-related majors, but it could also include areas of math and statistics. Training in business or human behaviour is also common, which bolsters more accurate conclusions in their work.

There are many paths to landing a career in data science. A typical data scientist goes through a four-year bachelor’s degree in IT, computer science, math, physics or any related field. However, if you are set on becoming a data scientist, some schools do offer data science degrees. This degree will give you the necessary skills to process and analyse a complex set of data, and will involve lots of technical information related to statistics, computers, analysis techniques, and more. Most data science programs will also have a creative and analytical element, allowing you to make judgment decisions based on your findings.

If you already have a degree, you may consider the option of completing your master’s degree in Data Analytics. The master’s degree would typically takes you 1.5 years to complete (or lesser if you have relevant bachelor’s degree applicable for credit exemptions). Students typically take on a master’s degree in Data Analytics for a change in career option or are already a data analyst looking to improve their skillsets and knowledge to be a data scientist.

If data scientist does sound like a career you want to pursue on in the future, contact us![:]

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