The advancement of technology and its incorporation into our lives has led to the generation of data in large quantities. The data are obtained from means such as mobile phones, social networks, e-commerce sites, health surveys, Internet searches, etc. The availability of large datasets paved the way for Big Data, a field that refers to the vast amount of information available. which can be used in various sectors such as finance, marketing, logistics, etc. obtain information and produce better results. Active smartphone data traffic is expected to multiply by five, from 1.4 gigabytes (GB) per month in 2015 to 7 GB per month by 2021. By 2021, 99% of the region’s mobile traffic will be given.

Listed below are some real-life examples of data science application

Internet Research

Every time we have to find a service or product, we try to find it using search engines like Google, Yahoo, Bing etc. These search engines use scientific data and algorithms to provide us with the best match in a very short period of time. Google now processes more than 40,000 search queries per second on average, translating into more than 3.5 billion searches per day (Source: www.internetlivestats.com). Options and better search speed, eliminating unnecessary data before indexing

Recommendations

Recommendation systems apply data science to provide recommendations to users. The most appropriate example is Amazon’s recommendation engine, which provides users with a custom Web page when they visit amazon.com. Recommendation systems are not only used in e-commerce, but also in other applications, such as recommending songs and events for products and dating profiles. Recommendations are made based on a user’s previous search results. Amazon Prime Day 2016 reported sales of approximately 636 items per second)

Some of the advantages of using data analysis in referral systems are:

• The ability to offer a unique personalized service to the customer.
• Increase sales, click through rates, conversions, etc.
• Opportunities for promotion, persuasion.
• Get more knowledge about customers.

Who can forget suggestions about similar products on Amazon? They not only help you find relevant products from billions of products but also add a lot to the user experience.

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Image recognition

Recognizing an image involves sorting data using many data points. By this technique, we can classify a complete image or things within an image.

Did you realize that Facebook offers suggestions to tag your friends when you send an image? Also, Google searches for images by uploading them. This is possible due to image recognition.

In addition, there are free databases available such as ImageNet and Pascal VOC. These databases are made up of millions of tagged images of what’s inside the images; Imagenet contains more than 14 million tagged images that are freely available.

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Games

There are more than two billion video game players in the world, and Electronic Arts, which has 275 million active users, generates approximately 50 terabytes of data per day.

There is a huge amount of data generated by social games, whether it is an online social game on Facebook, a game played on an offline PlayStation or an Xbox game. A large amount of data conforms to all the actions of the players, such as the way they interact, the duration of their games, the times, who play together, etc. Data analysis teams in the gaming industry extract this kind of information from their Games and analyze them to attract more customers, increase turnover, keep players spending more time, and improve the overall gaming experience.

Some of the companies that have used data science to provide an excellent gaming experience are EA Sports, Zynga, Sony, Nintendo, Activision-Blizzard, etc.

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Planning the airline route

Data science tools are being used to monitor changes in flight rates, depending on demand.

Data analysis has also been of great importance in the aviation industry to predict flight delays, either to stop or disrupt the flight directly. It also helps define new customer programs and identify operational strategies for improvement.

Based on the data generated and analyzed, algorithms are created that can predict future price movements based on a number of factors, such as seasonal trends, demand growth, special offers and air deals.

Hopper, one of the new aviation companies, uses data science to help people book the cheapest flights using predictive analytics.

There are numerous data analysis applications. Data science can change the play of some industries, helping digital transformation, enabling organizations to take advantage of the big data and use it to create opportunities and innovations.

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