Top 10 Applications of Data Science

Applications of Data Science

1. Airline Route Planning: 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. The high rise in air-fuel prices and the need to offer a heavy discount to customers has further made the situation worse. It wasn’t for long before airline companies started using data science to identify strategic areas for improvements.

2. Fraud and Risks Detection: One of the first applications of data science originated from the Finance discipline. Companies were fed up with bad debts and losses every year. However, they had a lot of data that use to get collected during the initial paperwork while sanctioning loans.

3. Delivery Logistics: Logistics companies like DHL, FedEx, UPS, and Kuehne+Nagel have used data science to improve their operational efficiency. Using data science, these companies have discovered the best routes to ship, the best-suited time to deliver, and the best mode of transport to choose. Thus leading to cost efficiency and many more to mention. Furthermore, the data that these companies generate using the GPS installed. It provides them with a lot of possibilities to explore using data science.

4. Uber’s Taxy Service: Uber is a smartphone-app-based taxi booking service that connects users who need to get somewhere with drivers willing to give them a ride. The service has been hugely controversial, due to regular taxi drivers claiming that it is destroying their livelihoods and concern over the lack of regulation of the company’s drivers. This hasn’t stopped it from also being hugely successful – since being launched to purely serve San Francisco in 2009, the service has been expanded to many major cities on every continent except for Antarctica.

5. Price Comparison Website: At a basic level, these websites are being driven by lots and lots of data which is fetched using APIs and RSS Feeds. if you have ever used these websites, you would know the convenience of comparing the price of a product from multiple vendors in one place. PriceGrabber, PriceRunner, Junglee, Shopzila, and DealTime are some examples of price comparison websites. Nowadays, price comparison websites can be found in almost every domain such as technology, hospitality, automobiles, durables, apparel, etc.

6. People Analytics: This application of analytics helps companies manage human resources. The aim is to discern which employees to hire, which to reward or promote, what responsibilities to assign, and similar human resource problems.

7. Portfolio Analytics: A common application of business analytics is portfolio analysis. In this, a bank or lending agency has a collection of accounts of varying value and risk. The accounts may differ by the social status of the holder, the geographical location, its net value, and many other factors. The lender must balance the return on the loan with the risk of default for each loan.

8. Risk Analytics: Predictive models in the banking industry are developed to bring certainty across the risk scores for individual customers. Credit scores are built to predict an individual’s delinquency behavior and are widely used to evaluate the creditworthiness of each applicant. Furthermore, risk analyses are carried out in the scientific world and the insurance industry.

It is also extensively used in financial institutions like Online Payment Gateway companies to analyze if a transaction was genuine or fraudulent. For this purpose, they use the transaction history of the customer. This is more commonly used in Credit Card purchases, when there is a sudden spike in the customer transaction volume the customer gets a call of confirmation if the transaction was initiated by him/her. This helps in reducing loss due to such circumstances.

9. Digital Analytics: Digital analytics is a set of business and technical activities that define, create, collect, verify, or transform digital data into reporting, research, analyses, recommendations, optimizations, predictions, and automation. This also includes the SEO where the keyword search is tracked and that data is used for marketing purposes. Even banner ads and clicks come under digital analytics. A growing number of brands and marketing firms rely on digital analytics for their digital marketing assignments where MROI (Marketing Return on Investment) is an important key performance indicator.

10. Security Analytics: Security analytics refers to information technology to gather and analyze security events to understand and analyze events that pose the greatest risk. Products in this area include security information and event management and user behavior analytics.