13 Amazing Uses of Data Science Today
Some of the best uses of data science in the modern world.
Take a look at our data and analytics roles
When we speak of search, we think ‘Google’, but there are many other search engines like Yahoo, Bing, AOL, Duckduckgo etc. These search engines use data science algorithms to deliver the best results for our search query in a fraction of a second. Furthermore, Google processes more than 20 petabytes of data every day. Without data science, Google would not have been the ‘Google’ we know today.
Digital Advertisements (Targeted Advertising and re-targeting)
From display banners on websites to digital billboards at airports- almost all of them are decided using data science algorithms. Hence, why digital ads have significantly higher CTR than traditional ones. They can be targeted based on the user’s past behaviour.
The suggestions about similar products on Amazon are not only to help find relevant products from billions of products available to them but also add a lot to the user experience.
Many companies have fervidly used this engine/system to promote their products/ suggestions by users’ interests and the relevance of information. Internet giants like Amazon, Twitter, Google Play, Netflix, LinkedIn, IMDB, and more, use this system to improve user experience. The recommendations are made based on previous search results from a user.
You upload your image with friends on Facebook and start getting suggestions to tag your friends. This automatic tag suggestion feature uses a face recognition algorithm. Similarly, using WhatsApp web, you can scan a barcode in your web browser using your mobile phone. In addition, Google allows you to search for images by uploading them. It uses image recognition and provides related search results. To learn more about image recognition, check out this fantastic (1:21) mins video:
Some of the best examples of speech recognition products are Google Voice, Siri, Cortana etc. Using speech recognition feature, even if you aren’t able to type a message, your life won’t stop. Speak out the message, and it will convert to text. However, sometimes, you wouldn’t realize speech recognition doesn’t perform accurately.
EA Sports, Zynga, Sony, Nintendo, and Activision-Blizzard have led the gaming experience to the next level using data science. Game design uses machine learning algorithms that improve/upgrade themselves as the player moves up to a higher level. For example, in motion gaming, your opponent (computer) analyses your previous moves and shapes the game accordingly.
Price Comparison Websites
At a basic level, these websites use lots and lots of data 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, Shopzilla, DealTime are some examples of price comparison websites. Nowadays, you can find price comparison websites in almost every domain, such as technology, hospitality, automobiles, durables, apparels etc.
Airline Route Planning
Airline Industry across the world is known to bear heavy losses. Except for a few airline service providers, companies struggle to maintain their occupancy ratio and operating profits. Moreover, the high rise in air-fuel prices and the need to offer customers heavy discounts have worsened the situation. So it wasn’t long before airline companies started using data science to identify strategic areas for improvement. Now using data science, airline companies can:
- Predict flight delay
- Decide which class of aeroplanes 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.
Southwest Airlines and Alaska Airlines are among the top companies that have embraced data science to change their work.
Fraud and Risk Detection
One of the first applications of data science originated from the Finance discipline. Companies didn’t want bad debts and losses every year. However, they had a lot of data collected during the initial paperwork while sanctioning loans. So they decided to bring in data science practices 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 analyze the probabilities of risk and default. Moreover, it also helped them push their banking products based on customers’ purchasing power.
Who says data science has limited applications? Logistic companies like DHL, FedEx, UPS, and Kune+Nagel have used data science to improve 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 these companies generate using the GPS installed provides them with many possibilities to explore using data science.
Additionally, apart from the applications mentioned above, data science has uses in Marketing, Finance, Human Resources, Health Care, Government Policies and every possible industry where data gets generated. For example, using data science, the marketing department of companies decide which products are best for Upselling and cross-selling based on the behavioural data from customers. In addition, data science can quickly answer the wallet share of a customer, which customer is likely to churn, which customer should pitch for a high-value product, and many other questions. Furthermore, finance (credit risk, fraud), Human Resources (which employees are most likely to leave, employees’ performance, deciding employee’s bonus) and many other tasks use data science.
Content by Analyticsvidhya
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