Data Science is growing at an exponential rate to become a part of almost every industry. It’s not just limited to the online world of search engines but rather has detailed expansion into healthcare, finance and even Transport. Whether it is something as simple as hailing a cab online, or something as complex as medical image screening for tumours. Data science is everywhere.
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With the advent of technology and the beginning of a digital world, there are impressive data science applications everywhere. These applications have elevated our way of living.
In a world where data is being produced at the rate of 1.7 MegaBytes per second for each person alive in the world , you can imagine its impact. With data being the new fuel, the digital impact left by people online is immense. Organisations make use of this data through data science technology to bring about positive changes in society. Read on to find out more about the impressive data science applications
Data Science Applications
Data science application in Healthcare
The best among the multitude of data science applications has to be the one in the healthcare sector. It has been a boon to human civilization. It not only increases life expectancy but also aims to uplift the livelihood of a sick person. Let us explore some of the data science applications in healthcare
The foremost data science application in health care is that of Medical Imaging. Procedures like CT scans, X-Ray, MRIs are all very common now, but it wasn’t so before technology enabled it. Traditionally, the doctor physically had to look for abnormalities and flaws in the medical images. The abnormalities that may have been really minuscule and not visible to the naked eye were generally missed. Now, this can be avoided using deep learning technology in data science.
Advancements in image recognition and computing technologies with a surge in data have helped to detect flaws in the images faster. Procedures of tumours detections, artery stenosis, organ delineation and many different procedures through methods and BigData frameworks like MapReduce have assisted doctors in various ways.
Genetics and Genome Research
Data Science applications also have a major role to play in gene sequencing. Researchers wish to utilize data science technologies to find the connection between genetics, diseases and drug responses. They also wish to find the impact of DNA on an individual’s health.
Bioinformaticians and geneticists use data science to analyse the effect a drug may have on an individual’s gene. Various data science tools like MapReduce, SQL, Galaxy, Bioconductor, etc processes the genetic data and also reduce the time that it takes for gene sequencing.
The whole process of manufacturing or discovering a drug is quite tedious. The procedure of manufacturing a drug, testing it and then finally having the clearance to reach medical stores and the general public takes a lot of time. The expenditure is also huge.
Data science applications in health care have reduced the time and complexity of the process significantly. The algorithms also help how the drugs will react with specific genes and can provide insights into the success rate of the drugs.
Predictive analytics in Healthcare
Data science technologies help in predicting the deterioration rate in a patient’s health. Thus it helps in improving patient care, chronic disease management and increasing the efficiency of the pharmaceutical chains. They can also provide preventive measures on knowing the life expectancy of a disease.
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Data applications in Finance
Data Science applications in Finance was one of the earliest use of data science technologies in real-world applications. Since finance sectors also generate lots of data, they wished to do away with the traditional processes of paperwork. Data science algorithms have introduced innovative ways of analysing risk probabilities, by separating data using different variables like customer profiling, past expenditure, Annual Earnings and other variables.
Data science algorithms also help different banks suggest their banking products to people based on their purchasing powers. It also helps to create a more personalized experience for each customer based on their user experience, modification of financial preferences etc.
Even in Stock Market, data science application is very prominent. Using past data of different stocks and trends, they can predict what the future outcome will be like. This helps to analyze what the future prices of the stocks will be like across a set period.
Advanced Image Recognition
Image recognition is another among the trending data science applications that have seen tremendous uses. Social Media applications like Facebook use this feature extensively. Suppose you are uploading a picture of your friends on Meta (previously Facebook). Soon you are bombarded with suggestions of whom you should be tagging in that photo. This is an example of data science integration.
When an image is recognized by the algorithm, it analyses the picture and then analyses your friends on Meta. If any of the faces match with that in the picture, then they suggest the auto-tagging features.
Apart from this, Google also enables image search facilities. Through this, you can upload an image on google and search for similar pictures. Google lens is another data science application that makes use of the Advanced Image recognition feature.
Speech recognition is all the rage right now. Home-assistant speakers like Google Home, Amazon Alexa helps recognize the voice and implement actions based on that. Simply one of the most innovative applications among the new data science applications. Even voice assistants on mobile phones like Siri or Microsoft’s Cortana only gets better as they receive more data. From carrying out simple commands like giving answers to questions like “what is the weather like today?” to carrying out complicated commands like switching on or off your home security systems.
Internet Search is probably the commonest example of the best data science applications. Internet is what revolutionised the world and made it more digitized. Google is the most famous search engine although there are many other popular search engines like Bing, Yahoo, AOL etc. without data science algorithms fused with the internet, the world would just not be the same.
The digital world owes most of its fame to targeted advertising. The most unique feature of the data science algorithm is specificity. Data Science technologies help us to choose our specific customers online. For example, if I were to go on Google today and searched for a mobile phone online, I would see ads pertaining to mobile phones on different websites. Whether it be Facebook or YouTube, they both show ads based on the demographics of the audience or the viewer, whatever the case may be.
Platforms like Google Ads and Facebook Marketing allows marketers to choose whom their advertisements would be shown to. Say if I am a matrimonial site that wishes to promote my services, then my ads would only be shown to singles in their late 20s to 40s or people who have expressed an interest in different matrimonial sites.
Digital Marketing is no doubt one of the best data science applications.
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Airline services also make use of data science applications. Using data science algorithms, the airline service can predict where the delays would happen, decide on the perfect airline to buy or make decisions like where the layover should happen. In addition to these logistic decisions, data science also helps airline identify their loyal customer and provide value-added services to them. This further helps in solidating their marketing strategies.
Given that the airline industry was pretty badly hit as an after-effect of the covid-19 pandemic, these scientific strategies helps them to make better strategic decisions.
The gaming industry makes the best example of data science applications. Most high-tech games can adapt themselves to levels based on the player’s skills set. First-class gaming companies like Zynga, EA Sports have upgraded their user experiences in the most innovative possible ways by making use of data science algorithms.
Data Science Applications in Retail and E-commerce
Data science has revolutionized the mainstream shopping experience. Whether you are a confused buyer or an impulsive shopper, the E-commerce sites have mastered the ability to convert even the normal window shoppers into seasoned buyers. E-commerce giant like Amazon study the past trends and the buying behaviours of a customer and accordingly suggests products to them. Using Statistical analysis, Amazon calculates the probabilities of a customer buying a certain product. If the probability is high enough, then amazon even transfers the product to a warehouse near the buyer.
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Data science applications in Delivery Logistics
Logistic companies like DHL, UPS, FedX, etc make use of data science algorithms to save up on time and expenditure and also provide the best customer experience. Data science applications in Delivery logistics helps these companies to find the best route for the shipment, suitable time to deliver the product, the best mode of transport etc.
Data Science Applications in Transport
Driverless cars are the innovation that is integrating data science algorithms. In driverless cars, the data is fed into the algorithm. Then the algorithm uses this data to analyze, the different parameters on road like the speed limit, speed blockages etc. These aim at minimizing road accidents.
Google has another special feature where you could type in a few words on the search engine and get a myriad of suggestions based on and around that topic. For example, If I were only to search mobile phones online, I would get suggestions for “mobiles under Rs. 10000” or “mobiles with 64 GB RAM”. This further pushes customers into spending more time on these search engines. Even on mailing services like Gmail, this feature is available while typing where there are autocomplete suggestions.
According to Glassdoor, data scientist was declared as the 2nd best profession in America . With tremendous growth opportunities, the US Bureau of Labor Statistics projects that by 2029, the employment rate of data scientists is supposed to grow by 15%, ( much higher than the 4% average of every other profession ).
With such opportunities, the number of data science applications is growing by the hours. As such it is a very lucrative industry to be a part of.
The best part about data science algorithms is that you need not even be an expert to reap the benefits. Even applications like Google Analytics and Instagram insights is enough to help you in your online journey. So whether you’re a small business owner or a data scientist at a giant tech organization, there is a perfect data tool for everyone.
 Becoming A Data-Driven CEO | Domo. (n.d.). Domo. https://www.domo.com/solution/data-never-sleeps-6
 Best Jobs in America. (n.d.-a). Glassdoor. https://www.glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm
 Computer and Information Research Scientists: Occupational Outlook Handbook:: U.S. Bureau of Labor Statistics. (n.d.). US Bureau of Labor Statistics. https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm