Data helps analyze, identify, understand and enhance the business of various industries like Manufacturing, Banking, E-Commerce, Web predictions, Healthcare, Education, etc. Internet users have implemented Data Science as a part of their daily activities and companies are also implementing Data Science to make better business. Check out Data Science Courses for in-depth knowledge and understanding.
Top 10 real-life Applications of Data Science
Data science has become an essential part of every industry. It is the extraction of significant data from structured and unstructured source data sets using statistical algorithms and scientific methods. It helps companies understand current and future market trends and moreover customer expectations. You can find solutions to any problems, apply a strategic approach to problem-solving, identify business strategies, etc. Big data has revolutionized the way we look at data.
So in this blog, you will get to know about the top 10 real-life Data Science Applications to look out for:
Table of Content
- What is Data Science?
- Top Data Science Tools
- Top 10 Data Science Applications
- Weather Predictions
What is Data Science?
Data science is a field that is changing the decision-making of large companies. Unlike many traditional fields, it studies how to collect and analyze data to create business models. Data science helps identify patterns and analyze the data, which helps stakeholders to make better decisions about their business.
Data science techniques are based on the use of analytical tools and methods to extract and interpret data.
Top Data Science Tools
Data science involves the use of various tools designed to extract knowledge from multiple sources. Data science tools are software or application frameworks that help data scientists perform various data science tasks, such as data analysis, cleaning, visualization, mining, reporting, and filtering. Each of these tools comes with some of these applications.
Some of the top Data Science tools are:
- MS Excel
- Google Analytics
- Apache Spark
- R Programming
Top 10 Data Science Applications
Data science is evolving as one of the most challenging domains nowadays and therefore used in various areas. Various industries are implementing Data Science as the most integral part of their businesses. So we are going to discuss the top 10 real-life applications of Data Science:
- Healthcare– Discovering or manufacturing drugs is one of the complex processes in the field of healthcare. Pharmaceutical companies rely heavily on Data Science to solve their difficulties and create better medicines for patients.
Discovering a drug is a process involving high financial costs and a difficult testing process. Data science acts as a revolutionary process that provides accurate information to improve forecasting significance. Pharmaceutical companies use understandings gained from patient information such as mutation profiles and patient metadata.
- Banking– Data science plays an important role in collecting, summarizing, and predicting customer databases for detecting fraud. Before the emergence of Data Science, it was not possible to analyze customer records to get accurate information. Artificial intelligence and Machine Learning can help banks fight fraud.
For example, you can build data models to analyze credit card fraud to gain insight into the data and identify transactions as fraudulent or authentic based on information such as purchase amount, location, merchant, time, and other information.
- Education– Continuous monitoring and updating are essential for the proper functioning of the education system. Teachers should monitor the students to improve their performance. They have to see what subject the student is facing issues. They should maintain detailed statistics of students’ attendance and grades.
So that’s why Data Science can be used in this context to help teachers analyze student behavior and updates. A graphical representation allows them to keep track of which topics are in development and which are not. So Data Science can help continuously monitor and track student performance.
- Policing– Social media provides the police with tools for early detection and prevention of crime. But with billions of people using social media, detecting or finding out crimes are impossible. Advanced Data science tools, such as Machine Learning algorithms, can analyze billions of texts and posts that are spreading hatred or committing any crime.
- E-Commerce– These systems are based on Machine Learning models that use statistical algorithms to analyze historical data and make accurate predictions. This helps businesses increase engagement on their websites by targeting potential customers based on their preferences.
- Weather Predictions– Data Science is also playing an important role in the proper analysis of meteorological data using models, which can predict natural disasters such as floods. It collects information such as the condition of the surrounding, roads, and the number of rainfall records in the past.
- Transport– There is a wide variety of transportation systems that can be analyzed and managed by Data Science. Applications in the railways, airways, or roadways include booking, security optimization, scheduling and booking, network optimization, ticket management, etc. Data available from passenger services management, reservation system, CCTV, and security systems can be used as an advantage to deliver businesses. Moreover, customers’ needs are also satisfied without any inconveniences.
- Web Search– With the help of Data Science, the Data Scientists design algorithms to analyze and identify customers’ data related to their search history, basic interested fields, and moreover previously shopped items.
Also, the system identifies relevant websites to post ads for the relevant marketing according to the previous search history or most visited sites. With the help of digital ads, the click-through rate (CTR) of a website grows by a high frequency and it leads to the increasing value of the business and enhances the existence of the company in the market.
- Sports– Using Machine Learning models, a player’s performance can be determined, and what position can be better on the match day can also be analyzed. This model will be built on the player’s statistics from the basic level and most importantly, it can find out how well that player performed against the rival team, etc.
- Manufacturing– Predictive analytics is one of the factors that help companies predict future product ranges based on customer needs. For manufacturing companies, data science enables accurate analysis of all factors that affect business growth.
Data scientists study data about customer needs and predict future trends. Based on these predictions, the company switches to improve its manufacturing.
This brings us to the conclusion of the Top 10 real-life Data Science Applications.
We discussed what Data Science is, along with the top Data Science tools used and the various applications which are not only enhancing various industries for improving their businesses but also, almost every internet user is making full use of Data Science in their daily lives.