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Top 8 Data Science Applications

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Data Science Applications

The field of Data Science is filled with wonderful applications. In this modern era of digitization, Data Science is making a huge difference in making businesses successful. Not only in business but fields like healthcare, aeronautics, robotics, medicine, etc., Data Science is the game-changer.

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1. Education

From earlier civilizations, education has been one of the key aspects of transforming the lives of people. It has helped innumerable people shape their careers and succeed in their lives. Now, education is one of the sectors where Data Science is making drastic changes in improving the entire system and the performance of students, teachers, and other key stakeholders. For example, with Data Science, the data of teachers such as their qualifications, student ratings, the effect of their teaching on the improvement of exam results, etc. are collected, analyzed, and used for further performance enhancement.

Next, the data of students such as the previous result, the current result, marks in individual subjects, etc. can be made useful for analysis. They are collected and then, with the help of Data Science tools for analysis and visualization, we try to extract valuable information to understand the scope for improvement.

When we talk about education, we cannot skip mentioning generative AI tools like ChatGPT, and Google Gemini that are changing the way students used to learn. Today, if students come across any doubt, they can prompt their query and the gen-AI tools will help them understand the feasible solutions.

Here are a few more areas of education that data science is providing resolve for:

  • Students can be provided with custom study plans by analyzing factors such as their scores, interest areas, faculty reviews, etc.
  • Data Science is helping educators design course curricula as per the analysis of students’ IQ levels and performance.
  • Institutes can track the performance of faculties based on student reviews, results of students, improvements by the weak students, etc.

Data Science application is thus helping a lot in improving the current education system.

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2. Airline Route Planning

One of the areas where Data Science is revolutionizing day-to-day business activities is the Airline industry. For a very long time, the Airline industry has been bearing a substantial decline in revenue generation, and then Data Science emerged as a savior. Previously, due to competition, the airline companies used to provide discounts to customers to attract them. Also, due to the high rates of fuel and the lack of proper analysis for the delay of flights, destinations, halts, optimized routes, etc., airlines were unnecessarily spending a lot on extra fuel.

To give you an example, Southwest Airlines used data science practices to minimize fuel consumption by strategically analyzing past fuel usage data. They created 8 predictive models that used time-series techniques and neural networks to produce 9600 projections for monthly fuel usage. (Source : NASSCOM Community)

Similar to the above example, with the help of the application of Data Science, many airline agencies have started analyzing the data of their business to strategically improve the sectors, due to which they were bearing heavy losses. Data Science has helped airlines in the following ways:

  • Identifying potential customers to offer calculated discounts, instead of providing discounts to everyone
  • Deciding on the optimized routes by analyzing the traffic on different routes. It helps in saving expensive fuel that gets unnecessarily exhausted otherwise
  • Predicting delays in flight
  • Setting the cost of flights as per seasons, festivals, and the number of travelers. This is done by analyzing the number of potential travelers and frequent travelers
  • Creating new routes to generate more revenue for the airline companies

This is how the application of Data Science is optimizing the profits of the airline industry.

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3. Healthcare Industry

The advancement in medical science has revolutionized the healthcare industry. There are fast and effective treatments for almost all diseases. However, there are areas where Data Science is helping the healthcare industry in efficient diagnosis, data management, medical research, etc. through data analysis and visualization.

The areas where the Data Science application in healthcare is playing a major role are as follows:

  • Patient Diagnosis: Data Science helps doctors monitor patients’ health with the help of IoT devices. These wearable devices help monitor various medical conditions such as heart rate, body temperature, blood pressure, etc. These devices send patients’ data to concerned doctors for medical analysis. This helps doctors take the necessary steps for treating patients accordingly.
  • Drug Research and Creation: For creating a pharmaceutical drug, it takes a lot of research, time, and money. Also, there are millions of test cases required for research. Using Data Science, we can process all these test cases and make predictions on the success rate of these, based on certain parameters used for evaluating drugs in less time. With this application of Data Science, we can successfully create highly effective medicines.
  • Medical Image Analysis: This is one of the interesting applications of Data Science, which is rapidly changing the way doctors do patient diagnoses. With the help of medical image processing, a machine predicts diseases such as cancer, tumor, organ delineation, and many others.
  • Managing Patient Data: Apart from the other applications of Data Science, it helps in managing patient data. The patient data is stored in databases and can be used in the future for the analysis of several medical conditions and the improvement of medical diagnosis and treatment.

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4. Delivery Logistics

When it comes to delivery logistics Data Science is not far behind the race. Many companies use data for optimizing their business operations. It helps in the analysis of profit generation, the causes of loss, the best route for delivery, the time required, and the scope for improvements. Other than that, the application of Data Science in delivery logistics helps companies analyze the market trend and increase their competence. Further, with the help of route optimization, the number of deliveries increases and the freight cost reduces.

Through this, companies can boost their profits. This is how the application of Data Science plays a major role in logistics.

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5. Banking and Finance

As we all know, the sector of banking and finance is prone to financial fraud and theft. This happens due to the lack of proper analysis of customer data. Since there are millions of records of customers in databases, it becomes a difficult task to track all of them.

This is where the application of Data Science in banking and finance comes into the picture. It helps organizations efficiently process data.

By processing the data, the system can analyze individual customers’ financial history, loans, income, and debt clearance. Data science helps in finding suspicious behaviors in transactions using fraud detection algorithms. Further, the application of Data Science in Finance helps in the following ways:

  • Stamping out Tax Fraud: The economy of a nation depends on its taxpayers. Governments need taxation to maintain the economic infrastructure of countries. If there occurs fraud activity related to taxation, then it directly affects every citizen of a nation. Therefore, governments have started implementing Data Science to analyze citizen data to prevent tax fraud. With the application of Data Science, the income tax departments keep track of the income and calculate the tax. If the calculated tax is not collected, they track the suspicious taxpayers to take action against them.
  • Credit Scoring: Credit scoring in data science is a statistical technique used in the banking industry to assess the creditworthiness of individuals applying for loans or credit. It involves analyzing various factors such as credit history, income, debt-to-income ratio, and payment patterns to assign a numerical score that represents the likelihood of the borrower repaying their debt. The credit scoring range typically varies from 300 to 850, where higher scores indicate lower credit risk and vice versa. Lenders rely on credit scores to make informed decisions about approving or denying credit applications and setting interest rates.

Apart from the above-discussed applications of Data Science in banking and finance, banks use data to identify their potential customers. They provide certain benefits to their potential customers to maintain a lifetime customer relationship.

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Have you ever noticed when you type anything on Google Search it shows the keyword and the relevant topics related to it? Google picks up the most relevant and highly searched long-tail keyword related to your typed keyword. It helps in optimized searching to get better results. This is a type of filtered Internet search and also one of the wonderful applications of Data Science.

It is only possible with the help of Data Science. Google collects and stores the data of search history to analyze and visualize it. Then, it uses algorithms and techniques that apply filters to the data to check the frequency of the searched keyword and related topics to show you the best results.

Prepare yourself for the Top Data Science Interview Questions and Answers Now!

7. Product Recommendation Systems

Product recommendation is an effective way of converting leads into sales. All industries based on sales use recommendation systems for improving their profitability. But, how do these recommendation engines work? It is again a Data Science application.

Recommendation System

With the help of multiple tools and techniques of Data Science, a system records customer data such as browsing history, products selected for purchase, items added to the cart, etc. Then, it tries to understand the patterns in this data to filter the customers who are likely to make a purchasing decision, i.e., the system filters the leads that might convert into sales. After finding out such potential customers, the recommendation system starts suggesting products to them. It advertises the products on different websites browsed by the same customers.

According to Rejoiner, 35% of Amazon’s sales are driven by recommendation engines. That explains how enormous this application of data science is for the E-Commerce sector. Here are few more organizations that use recommendation systems: Flipkart, Zalando, and Lenskart. Through this application of Data Science, companies are becoming capable of making a successful business model with good revenue generation.

8. Digital Marketing and Advertising

In the 21st century, digital marketing and advertising have become major tools for growing any business. The digital marketing field has become a billion-dollar industry in the past few years. This immense growth is not possible without Data Science. The Data Science application in digital marketing helps organizations advertise their products to the right customers.

Data Scientists design algorithms to analyze and visualize customers’ data related to their search history, interests, and previously shopped items. Also, the system identifies relevant websites to post ads for marketing. With the help of digital ads, the click-through rate (CTR) of a website increases by a high frequency. Not only that, modern-day marketing field: Performance Marketing is built upon the notion of using data to reach the right customers online. Through digital marketing, the value of the business increases as advertising enhances the visibility of the company in the market.

The applications of Data Science in various sectors are playing a key role in changing the world by using various Data Science methodologies. These methodologies are related to data wrangling, analysis, visualization, and many more. These integrate with software, web applications, and mobile applications, which makes them efficient. This is all about the applications of Data Science.

If you have any doubts or queries related to Data Science, do a post on Data Science Community.

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