Data Science and its possible use cases
In previous posts we have already talked about data science and what a data scientist does. That is why today’s post will be dedicated to delving into this topic, and why it has become so important. In turn, we will mention the main use cases of data science.
How does data science work?
Simply to refresh what we had mentioned in previous posts, data science is a discipline that covers various fields of expertise. Its ultimate goal is to make sense of raw data, and to achieve this, data scientists must extract the most relevant information from them. Through skills in data engineering, mathematics, statistics, computer science and data visualization.
Main use cases of Data Science
The use cases of this science are very varied, in fact, they change according to the objective of the company and the industry. That is why, it could be said that this science allows any organization to facilitate decision-making.
In turn, it is important to note that data-driven decisions can lead to higher profitability and better operational efficiency, business performance, and even better workflow.
Use cases of Data Science in various sectors:
- Human resources: You can help human resources teams to recruit staff. Because, internal application processing and data-driven aptitude tests manage to ensure faster and more accurate selections.
- Marketing and sales department: These can extract customer data to improve the conversion rate or create specific campaigns for each one.
- Banking industry: This industry, for example, uses this science to improve fraud detection
- Shipping companies: These companies use this data to find better routes, schedules and modes of transport.
Conclusions…
It can be said that Data Science is an emerging field within companies. Since the identification and analysis of large amounts of unstructured data can sometimes be too complex, expensive and time consuming for companies. However, making decisions under this concept can lead you, without a doubt, to greater profitability.