If we look at business based data science i.e. business analytics there are several options to create an impact, like Data-driven decision-making, predictive analysis, customer analysis, market intelligence, and most important and in-demand part, Risk assessment, and fraud detection. Every business emphasises the areas mentioned above and these sectors are handled by data scientists.
The main role of a data scientist in this sector has to be the following:-
1. Provide all the required information that will help in better decision-making.
2. Plot both positive and negative trends to check the position of the company
3. Presenting the required solution on any given financial decision after doing a good analysis.
4. Making sure that the clients are satisfied with the service that is provided and checking how the company can improve these trends.
In the medical field, we can apply data science for the identification and early detection of critical disorders, and create and model clinical decision support systems, these will eventually impact improving treatment efficacy, minimizing side effects, and tailoring therapies to individual patients. Not only this but we can provide patients with personalized treatment by tracking down their genetic data and taking measurable health precautions.
To explain this clearly, let’s take an example of a project that is based on machine learning and data science. Heart attack detection is one of the prominent advancements that can be made using data science. The steps involved in this are quite simple. First, a huge data set is collected, with information like:-
After getting a hold of this data, we can then perform several operations and make a very efficient heart attack prediction model.
Large amounts of textual data in the social sciences and humanities can be analyzed using data science techniques like text mining and NLP.
Uses, such as analyzing literary works for thematic analysis, examining historical texts for cultural analysis, and using social media data to study public sentiment. This will be a groundbreaking work when technology and history will work together.
When you get to work in the field of data science, you will be able to see the emerging sectors of AI and ML. A lot of companies will offer you several positions, like data analyst, data governance head, and data engineer where you will apply the major concepts of Data mining, warehousing, wrangling, etc.
With AI coming into play the task of data scientists in their field has become more clear and strong. For every machine, chatbot, robot, or AI that they make they will require data. Not just any simple and solved data but huge datasets that can be handled by only an expert.
Cloud computing and cyber security is without a doubt the most in-demand and growing area of IT. One of these fields is associated with data storage and the other one with data security. And where ever data is involved a data scientist is automatically involved.
When we talk about cloud computing, Data scientists focus on gathering and analyzing data stored in databases on the cloud. They also help to store and arrange information in cloud computing data storage locations.
If we look into Cyber security, data scientists collect information about the security of a company’s online and internal information. They assess data regarding safety to determine how easily outside sources may get the information. Cybersecurity data scientists can help
other cybersecurity professionals ensure an organization’s information stays private and secure.
To sum up, data science presents numerous exciting prospects for college students.
Students can position themselves at the forefront of a rapidly evolving field with a wide range of opportunities by learning data science skills. It is impossible to overstate how important data science is to a variety of fields, including business analytics, healthcare, social sciences, and humanities. Graduates with experience in data science will find it easier to find
employment as the demand for data scientists continues to grow.
The options for learning data science are numerous for college students. Data science boot camps, online learning resources, and formal education programs all provide structured curriculums and thorough coursework. Additionally, developing one’s skills through independent study using online resources, competing in data science competitions, and pursuing internship and research opportunities.
Students have the chance to connect with professionals in the field and stay current on new developments thanks to networking and professional development opportunities. Students
who explore these options can build a solid foundation in data science and open up exciting career opportunities.
College students must grasp the value of data science for their academic endeavours and future careers in this era of data-driven decision-making. Students who embrace data science can contribute significantly to their fields, spur innovation, and become valuable
members of society.
In order to advance their knowledge and abilities, aspiring data scientists should take advantage of the opportunities that are presented to them. College students can embark on a rewarding journey in the dynamic field of data science if they are determined, curious, and passionate about harnessing the power of data.
Article by Anushka Ranjan, Team edSlash.