How Data Science Has Changed Everyday Life for the Better

Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Mining large amounts of structured and unstructured data to identify patterns can help an organization rein in costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage. Some companies are hiring data scientists to help them turn raw data into information.
Data scientists must possess a combination of analytic, machine learning, data mining and statistical skills as well as experience with algorithms and coding.

Application of Data Science

Here’s how Data Science comes to our rescue in our everyday routine.

Recommender Systems

Who can forget the suggestions about similar products on Amazon? They not only help you find relevant products from billions of products available with them, but also adds a lot to the user experience. The recommendations are made based on previous search results for a user.

Internet Search

Search engines make use of data science algorithms to provide the best search result for searched query in fraction of seconds. Considering the fact that, Google processes more than 20 petabytes of data everyday. Had there been no data science, Google wouldn’t have been the ‘Google’ we know today.

Healthcare

Today fitness trackers and apps already help people lead a life that is more active, eat healthier and control their weight – and this is only the beginning. Already such devices monitor heart rate, sleep patterns and other vital signs that can be interpreted to serve other healthcare purposes and provide a diagnosis. The best cure is prevention, and with big data science, everyone will be able to keep their health in check.

Logistics

Logistic companies like DHL, FedEx, UPS, Kuhne+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, the best mode of transport to choose thus leading to cost efficiency, and many more to mention. Further more, the data that these companies generate using the GPS installed, provides them a lots of possibilities to explore using data science.
Airlines schedule flights, predict delays based on precise weather forecasts and estimate the number of seats they are going to need for each direction based on seasonal fluctuations, competitors’ actions, latest social trends or political events. There are also mechanisms that allow them to decide on the class of planes they will need to purchase in the future.

Image Recognition

Today face recognition is not that big a deal. It offers you to tag your friends on social media photos; it enables goofy masks in Snapchat, Instagram and webcam programs. Lots of fun and nothing substantially useful. However, this can be a powerful tool of law enforcement in the future. Already this feature is making its way into security systems – in flagship models of modern smartphone, you may choose face recognition to unlock your device. In future, it can be used to identify suspects and find missing persons.

Data science and Python

Why Python is usful for Data Science? Python is a powerful, flexible, open source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis. Its simple syntax is very accessible to programming novices, and will look familiar to anyone with experience in Matlab, C/C++, Java, or Visual Basic. Python has a unique combination of being both a capable general-purpose programming language as well as being easy to use for analytical and quantitative computing.

Python is easy for analysts to learn and use, but powerful enough to tackle even the most difficult problems in virtually any domain. It integrates well with existing IT infrastructure, and is very platform independent. Among modern languages, its agility and the productivity of Python-based solutions is legendary. Companies of all sizes and in all areas — from the biggest investment banks to the smallest social/mobile web app startups — are using Python to run their business and manage their data.

Because of growing importance and scope of data science, many are opting for business analytics and data science certification courses. Data Science is changing the world, and if you are passionate about this fascinating discipline, then this is the time to enroll yourself in a data science course.

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