Applications of Data Sciences
Applications of Data Sciences
Fraud and Risk Detection: The earliest applications of data science were in Finance.
Companies were fed up of bad debts and losses every year.
However, they had a lot of data which use to get collected during the initial paperwork while sanctioning loans.
They decided to bring in data scientists in order to rescue them from losses.
Over the years, banking companies learned to divide and conquer data via
customer profiling,
past expenditures, and
other essential variables
to analyse the probabilities of risk and default.
Moreover, it also helped them to push their banking products based on customer’s purchasing power.
Genetics & Genomics: Data Science applications also enable an advanced
level of treatment personalization through research in genetics and
genomics.
The goal is to understand the impact of the DNA on our health and find individual biological connections between
genetics,
diseases, and drug response.
Data science techniques allow integration of different kinds of data with genomic data in disease research, which provides a deeper understanding of genetic issues in reactions to particular drugs and diseases. As soon as we acquire reliable personal genome data, we will achieve a deeper understanding of the human DNA.
The advanced genetic risk prediction will be a major step towards more individual care.
Internet Search: When we talk about search engines, we think ‘Google’. Right? But there are many other search engines like
Yahoo,
Bing,
Ask,
AOL, and
so on.
All these search engines (including Google) make use of data science algorithms to deliver the best result for our searched query in the fraction of a second. Considering the fact that Google processes more than 20 petabytes of data every day, had there been no data science, Google wouldn’t have been the ‘Google’ we know today.
Targeted Advertising: If you thought Search would have been the biggest of all data science applications, here is a challenger
– the entire digital marketing spectrum.
Starting from the display on various websites to the digital billboards at the airports – almost all of them are decided by using data science
algorithms.
This is the reason why digital ads have been able to get a much higher CTR (Call-Through Rate) than traditional advertisements.
They can be targeted based on a user’s past behavior.
Website Recommendations: Aren’t we all used to the suggestions about
similar products on
Amazon?
They not only help us find relevant products from billions of products available with them but also add a lot to the user experience.
A lot of companies have fervidly used this engine to promote their products in accordance with the user’s interest and relevance of information.
Internet giants like Amazon, Twitter, Google Play, Netflix, LinkedIn, IMDB and many more use this system to improve the user experience.
The recommendations are made based on previous search results for a user.
Airline Route Planning: The Airline Industry across the world is known
to bear heavy losses. Except for a few airline service providers, companies are struggling to maintain their occupancy ratio and operating profits. With high rise in air-fuel prices and the need to offer heavy discounts to customers, the situation has got worse. It wasn’t long before airline companies started using Data Science to identify the strategic areas of improvements. Now, while using Data Science, the airline companies can:
Predict flight delay
Decide which class of airplanes to buy
Whether to directly land at the destination or take a halt in between
(For example, A flight can have a direct route from New Delhi to New York.
Alternatively, it can also choose to halt in any country.)
Effectively drive customer loyalty programs.