Admin | July 28, 2022
- Due to tremendous technological advancements, data science has become an essential part of many industries, including healthcare, e-commerce, finance, and gaming.
- The primary use of data science is to make predictive analyses and make appropriate business decisions.
- A data scientist collects, analyses, and processes organisational data to gain effective insights.
- A career in data science is highly in demand and is predicted to be the trendiest in the market in the upcoming years.
- Data science eligibility is not specifically defined. However, having a degree in data science, maths, or statistics may be helpful.
- Data science has a wide future scope as well as high-paying salaries.
- Coding is not essentially needed to start a career in data science.
Data science: Explained
What is data science? Data science is nothing but a blend of various tools such as machine learning, algorithms, automation, etc. It is a technological process that is used to derive meaningful data and helps in making business decisions. The technique allows businesses to analyse all the data using complex machine learning algorithms, which helps in building predictive business models. With the help of data science, businesses can effectively make appropriate decisions with a strategic project plan.
Roles and responsibilities of a data scientist
Now that you have understood what data science is in simple words let us start with the next point. So, what exactly does a data scientist do? The basic task of a data scientist is to analyse the business’s data to gain meaningful insights. The roles and responsibilities of these professionals may be different for every organisation. However, we have curated a list of the most common roles and responsibilities that they undertake.
As the name suggests, a data scientist must work with the organisation’s data. So, all the roles and responsibilities of a data scientist revolve around the respective organisation’s data. From extracting the data to finding meaningful insights, a data scientist needs to process the data to complete the entire process.
The roles that a data scientist needs to undertake while completing this entire process are given below:
- Collecting, preprocessing (structured and unstructured data), and analysing the data.
- Identifying the problems associated with the organisation.
- Build models and machine learning algorithms to showcase all the problems.
- Present all the data using various data visualisation techniques.
- Identify valuable data sources.
- Automate the data collection processes
- Discover the business trends and patterns.
- Combine all the predictive models using various ensemble modelling techniques.
- Find out solutions and strategies for various business challenges.
- Collaborating with the product development teams.
Application of data science with examples
We have listed applications of data science in various industries.
|1||Healthcare||Medical image analysis, drug development, virtual assistance/online chatbots, genetics and genomics, predictive modelling for diagnosis, etc.|
|2||Search engines||Google, Bing, Yahoo, Ask, etc.|
|4||Finance||Risk analysis automation|
|5||E-commerce||Flipkart, Amazon, Myntra, etc.|
|6||Image recognition||Auto-tagging of images|
|7||Airline route planning||Predicts flight delay, derives which tickets to buy, etc.|
|9||Delivery and logistics||Derives the best route for shipping, best mode of transport, etc.|
|10||AR and VR||Games like Pokemon Go|
How to get into data science?
Once you understand the roles and responsibilities of a data scientist, the next questions are how can one become a data scientist? What is the eligibility to get into data science?
So, there are no specific criteria for who can get into a data science field. All you need is a degree and the required practical skills to assess with the same.
|Masters degree in mathematics, statistics, data science, computer science, or any other related field.||– Strong maths and statistics|
– Strong analytical skills
– Proper knowledge of various programming languages such as Python, SQL, and R
– Well versed in using various data visualisation tools such as Tableau and Power BI
– Good foothold on machine learningSoft skills (communication and presentation skills)
The most important part here is to showcase your skills. So, try taking live projects and creating a portfolio of the same. Doing an internship will also be of additional benefit and help you land a good job. Apart from that, start networking with people already involved in the data science field. Note that networking is the key to a successful data science career.
Is data science a good career path for you?
First, find out whether you are passionate about making a career in data science. Start looking out for your interests and passions. If you are someone who likes Maths, Statistics, working with chunks of data, coordinating with a team, solving all business problems, etc., data science may be the right path for you to choose.
Data science is gaining popularity day by day. The increasing advancements in data science have increased the future demand for the same. It is, therefore, one of the most lucrative choices.
Why data science?
After reading all the above points, you may now have a clearer picture of a career in data science. If not, we have another solid reason for you to know why data science is among the best career options. The forecast predicted by the US Bureau of Labour Statistics shows that the data science field is more likely to grow by 28% by 2026. The constantly increasing growth in the field shows the increasing demand trend. It shows the data science field’s durability, scope, and longevity.
As a result, the salaries for any job role in the field of data science will go on increasing year by year. And the most amazing part is that you can also learn data science online through various platforms. Hence, if you want a secure, stable, as well as high-paying career, you can always choose data science as the perfect profession without any second thought.
Does data science require coding?
Many people in the data science field do not have a coding background. Recently, low-code and no-code data science platforms are getting popular. So, even if you do not have any prior coding experience, it is okay. You can still get into the field of data science. However, to keep making progress in your career, it is advisable to learn at least basic coding.
As the data science job market has been in tremendously high demand, you need to know coding to be able to compete with the ones who are already well-versed in it. There are a lot of coding courses and boot camps available online, where you can learn all the basics of coding. You must then consistently practice, take up coding projects and internships to keep learning more about the same.
What is the eligibility to get into the data science field?
There are a few requirements for entering the data science field.
- A strong background in computer science and mathematics
Data scientists have to be able to think abstractly and solve complex problems, so it’s important that they have a good understanding of how computers work and what makes them tick.
- Proficiency in analytics techniques and data mining techniques
You must know how to take raw data from sources such as sensors or other systems, clean it up so it’s usable, then make sense of it by analysing patterns and trends.
- Knowledge of programming languages
Finally, you’ll need experience with programming languages like Python or SQL (structured query language). These are used to query databases so you can ask questions about your data set, like “How many people bought Product X?”
Pursue M.Sc. in Data Science from Online Manipal
Today, data science is one of the trendiest career options in India as well as Abroad. Starting a career in data science without a relevant degree may not be easy. Most of you might be unsure of how to learn data science. You will need to learn various skills by taking up random courses online. However, Online Manipal has got it all for you under a single roof.
Now, you can do an M.Sc. in Data Science from the prestigious Manipal Academy of Higher Education (MAHE). The intent of this programme is to create smart data scientists depending on today’s market needs.