Data science requires making use of scientific models, algorithms and methods to extract information from the given set of data. Techniques are applied that are drawn from various fields like information systems, computer science, mathematics and statistics to name a few. Something that would take several hours for humans to predict outcomes can be done by data science applications in a couple of minutes. These applications have not only improved the efficiency in processing huge chunks of data but have also been very profitable. Companies, now, have in turn started marketing these tools very intelligently to customers who are ready to pay a premium to access the same.
These are some of the data science applications that have been extensively used in today’s age:
1. Advanced image recognition:
The medical space has seen massive progress in analyzing imaging to automatically detect faults in Magnetic Resonance Imaging (MRI), X-rays or Computed Tomography (CT) scans. In today’s era, high-end smartphones also use image recognition as a way to unlock the phone to protect sensitive information and prevent mishandling. Google also uses advanced image recognition to identify and locate the original source of the picture.
2. Airline Routing and Planning
Data science applications have been used extensively in the airline industry for multiple functions. The estimated time of arrival and any unforeseen delays can be easily tracked. The customer loyalty programs along with miles calculations are efficiently run by these applications.
3. Banking and Finance
One industry that has fully utilized these applications to the best of their advantage for maximum profits is banking and finance. Data science applications have transformed this industry by fraud detection, customer data management and segmentation. Not only have the applications helped in client profiling by detecting bad debts based on the customer’s ability to repay past debts, but it has also helped them market specific banking products to the appropriate target audience depending on the investment and behavioral patterns.
4. Transport and Logistics Providers
The logistics industry has grown at a massive rate attributing to tremendous increase in e-commerce and online shopping. Using data science, the courier and logistics providers have considerably reduced the cost by identifying the best and fastest possible routes for delivery, which in turn improves operational efficiency.
5. Voice Recognition
Siri and Alexa are the most popular examples of voice recognition. Whether it is typing a message, calling your friend, searching topics on Google or playing music, everything can be done in split seconds by just giving commands. These applications are constantly tested and developed from time to time to maintain the competitive edge since there is a new player in the market every single day. However, voice recognition can be tricky and could backfire too, but more often than not, it is easier and faster to use the function.
Data science course applications have come a long way, which in turn revolutionized so many industries and have just been constantly improving the efficiency of working. These applications have proven to provide a competitive edge against the peers by creating a reduction in cost as well as manpower.
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