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Home » AI » What is Data Science? Meaning, Examples, How to Get a Job, and Others

What is Data Science? Meaning, Examples, How to Get a Job, and Others

Data science has a wide range of applications in various fields starting from the finance sector to even healthcare as well. It can be used to predict the forecast of stock markets to even analyse data in motorsport racing like which sector of the track a driver is losing time and which line to take to have the maximum exit speed.

tech chilli logo by Tech Chilli Desk
Friday, 31 May 2024, 2:28 AM
in AI
What is Data Science

What is Data Science

Data science is a cross-disciplinary field that involves various processes and algorithms to extract desired data from a vast data pool. This involves analysing unstructured, complex data to find a particular pattern or record, or even to find a correlation among the data. 

Data science is present in almost every corner of today’s world. It is growing at a very rapid rate, as confirmed by the IDC as they have reported that the data pool is going to increase by 175 ZT by 2025. 

Since it is not humanly possible to manually analyse this huge amount of data, it is estimated that the requirement for data scientists will increase to 28% by 2026. With this huge requirement, the market for the data science industry is also expected to increase, and it is predicted that the global data market will reach a whopping $ 501 billion by 2027.

Thus, data science is a technical line that enables us to make various data-driven decisions and helps to improve efficiency and produce a productive outcome as desired.

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Types Of Data Science:

There are various applications of data science at the present age, however, the most common data science usage are : 

  1. Predictive Analytics: It is a scope of data science where certain programs are used to analyse the data to make certain predictions, hence the name predictive analytics. Data Scientists in this scope analyses the data using the means of statistics and various other machine learning processes to predict a forecast. It is one of the most common types of data science and has wide implications.
  1. Data Mining: This is a type of data science where data is being analysed to find a relationship between the data present in the data pool. Once a particular pattern can be found, the analysis can be done easily for those data. It is mainly used in unstructured and complex data.
  1. Big Data Analytics: This involves work that deals with huge amounts of data that cannot be analysed using simple algorithms or machine learning techniques. One has to be highly qualified to work in this role to analyse and process these big amounts of data.
  1. Machine Learning: It is a part of data science that involves using data to make the system learn about the pattern and make decisions based on it. With various types of data, it can learn and make predictions or even find patterns, and with every new task, it can learn and make more accurate results with every new task.

Application of Data Science in Real World 

Even though it is not possible for a normal human being to see where data science is being used, its usage is present in almost every sector of the world.

  1. Healthcare Sector: The Medical Sector has benefited a lot from data science. It can be used for analysing medical images, and genetics and also in research and development in the pharmaceutical field as well.
  1. Transportation: With the introduction of the ADAS system where the car has an integrated system to analyse whether there are any cars nearby or if any humans are approaching and safely brake to avoid a collision. Also, there are numerous brands like Tesla, which even have full self-driving ability. Data Science played a very integral part in these developments. It also helps in navigation and helps us to select which route to take while going from one place to another so that there is less traffic and hence less time to reach the destination.
  1. Marketing Sector: It plays a very crucial role in this field. Data Science helps to analyse the trends and patterns and helps to predict what action to take in order to increase sales. 

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Employment Scope in Data Science

In order to pursue one has to have an extremely analytical mind and be proficient in mathematics and computer science.

They also need to complete a bachelor’s or master’s degree in these aforementioned fields and participate in various internship programs and data science competitions.

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Also not to forget, if you are considering being a data scientist, then you must be well-versed in various programming languages like Python, SQL, etc. Some notable certifications that can help to have a good career in this field are 

i) Microsoft Professional Program in Data Science

ii) Cloudera Certified Associate

iii) IBM Data Science Professional Certificate

One of the leading job portals, Glassdoor states that the average annual salary of a data scientist is around 14,00,000 INR however it is different for other parts of the world depending upon the location and demand in that particular sector.

Some Interesting Facts about Data Science:

  1. From 2016-2026, there will ba 28% surge in demand for data scientists
  2. Data Science has a very wide scope and is not only limited to the tech industry
  3. It can also be used to mitigate poverty and increase disaster response rates.

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Advantages of Data Science:

There are several advantages of data science, however, the most notable facts are:

  1. Enhanced Decision Making: With the application of data science, it can help to learn from previous trends and provide us with a decision that would be very efficient.
  1. Improved Customer Experience: Data science can help identify marketing trends and analyze customer behaviour. Thus, in turn, we can strategically improve the services for an enhanced customer experience.
  1. Improved Risk Control: It helps an organization assess the risk factors and develop new strategies in order to reduce the risk and potential fraud as well.

Conclusion

Hence, we can easily see that data science has a vast scope and has applications in almost every day of work. From the transportation sector to healthcare, it can be used to analyse the data, improve certain conditions, and predict the forecast. One has to have an excellent knowledge of statistics and mathematics, along with various programming languages, to excel in this career path.

With such a radial increase in demand for jobs, the requirement for data scientists will also likely increase a lot in the upcoming years.

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