Top 10 Data Science Use Cases in Analytics
Data science refers to the leveraging of existing data sources as well as the creation of new data from which you derive useful information and actionable insight. Data science and data analysis vary because they use different approaches, focus on different elements, and use different tools.
A use case, in this case, refers to how a data scientist will use data science to accomplish their goal. Use cases contain three main elements: an actor, a system, and a goal. Analytics is the computational examination of statistics or data systematically. Here are some of the top data science use cases in analytics.
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1. Internet Searches
The goal of all search engines, not just Google, is to deliver to you the best results that fit your needs in the shortest time possible. Data science algorithms will analyze your previous search and internet use behavior to predict what you are looking for. It will leverage information such as your most visited websites, demographics, location, previous searches, and much more. That is why your search results may not match your friend’s results, even if you are searching for the same thing.
There are many use cases of data science in healthcare, from tumor and anomaly detection to drug development. One key example is AI-powered virtual assistants that can save you the task of going to the hospital by giving you a highly accurate diagnosis to treat your ailments. They leverage the information you provide (e.g., symptoms) with a network of information containing causes and symptoms to give you an accurate diagnosis. You are the actor, the virtual assistant is the system, and the diagnosis is the goal.
3. Speech Recognition
These days, you could be in bed and ask Siri or Google Assistant to switch on the smart lights, open your smart blinds or even turn on your coffee maker so that your coffee is ready by the time you get out of bed. The system takes input from you, analyses this input, and gives an output. Speech recognition is still evolving as people speak differently. So sometimes, the system may not correctly recognize what you are saying. However, thanks to speech recognition, you can do so much more even when your hands are tied.
4. Targeted Advertising
Many people have complained that they searched for an item once or twice, and they are now receiving advertisements for these products whenever they are on social media or different websites. This is an example of how marketing companies leverage your information and past behavior to increase their chances of getting customers. Marketing companies are some of the biggest data science users because they understand that many potential clients are on the internet multiple times a day. By studying their search patterns, they are able to market themselves to the most suitable clients.
5. Predictive Systems
You may have noticed that when you are on YouTube, the system will recommend similar videos to what you are watching or have been watching. Similarly, Netflix can use your past watching history to predict what you may be interested in next. Amazon can also recommend items you would be interested in based on past searches, either made by you or other users similar to you. These systems leverage your past behavior and actions and analyze existing similar products in their systems to give you better recommendations.
6. Image Recognition
One interesting feature in some search engines like Google is the ability to search using an image. This system will analyze the image to give you results that are related to the picture. Other uses of image recognition include when Google Photos groups photos containing similar people, how you can scan a bar code to get a particular result, and how Facebook can suggest who to tag in a group photo.
7. Online Dating
You may be surprised to know that your favorite dating website most probably uses data science and analytics to help bring the most likely candidates to you. They compare information such as interest, location, and peoples’ ‘types’ to help recommend people you with the most likely match. An example is Tinder, whose algorithms play matchmaker to help you meet people you are most likely to pick.
8. Fraud and Risk Detection
Besides the marketing sector, the finance sector is one of the biggest users of data science. For example, in the past, financial institutions had to manually sift through a lot of data to determine which people to give loans to. Now, with data science, AI algorithms will analyze these customers’ information from their past expenditure to how they paid previous loans to determine how risky it would be to give them a loan. All this is done in a very short period, which is why these days, loan approval can take a few minutes when in the past, it may have taken a few weeks.
9. Product Delivery
Thanks to e-commerce, the product delivery business is thriving. These organizations are made more efficient by product delivery. Product delivery companies can use big data to determine different elements, such as which routes to use at which times, the best times for delivery, and even the best modes of delivery to optimize their business.
10. Price Comparison Websites
Thanks to price comparison websites, price comparison has never been easier. Gone are the days when you had to manually visit different service providers and websites to compare these items’ prices. Now, there are websites to take data from different places and compare it for you, so all you have to do is pick.
If you want to learn more about data science and their use cases or even study it in detail as a part of your assignment, you can look for essays for sale on the topic online and use them for your research or paper.
As long as you use the internet, there is a high probability that data science is in place to make your experience more enjoyable and fitting to your needs. Data science is helping to make our lives easier. One can only wait to see what data scientists will use data science for in the future. It will most likely prove to be very useful in some fields like robotics and self-driving cars.