Applications of data science in real time world

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No matter what the stream/industry is, data is very important. Data collected from a particular industry can be used for analysis of patterns, trends, etc. This aspect of data leads to innumerable applications. This in turn has led to the development of data science as an important job avenue. Not only are the jobs created by data science considered to be lucrative, data science also paves a way to probe the innards of modern technology. The jobs related to the field of data science course and data analytics course are a direct manifestation of its real time applications.  Due to the continuous development of computing technology, the field of data science has gotten even more interesting. This means being a data scientist is not only rewarding in terms of financial aspects, but also in the aspect of job satisfaction. Some of the real time applications/possible avenues of data science are:

Intelligent internet searches:

This is a relatively well-known application of data science. Over the years, like many other internet technologies, the simple internet search has seen monumental advancements. The people behind major search engines like Google, Yahoo, Bing, etc. have altered their search algorithms from time to time to make searches more user-friendly. Initial searches were cumbersome. The user has to be certain of every keyword entered because a single error in a keyword would pop up a wrong search. The data collected by search engines and other online companies have been used in the determination of the nature of the searches and supplying the user with intelligent recommendations. This is the reason why almost all the related options related to a particular topic appear before typing the entire search string. Moreover, data science has also enabled using data from a particular location to determine the searches trending in a particular area and recommend it to users.

Image recognition:

 Image recognition has been around for quite a long time. However, the full potential of image recognition and advanced image recognition technology has been used by various social media platforms. Facebook is a good example of a social media site employing facial recognition. For uploading a photo on Facebook with friends, Facebook immediately suggests the user to tag his/her friends from the photo. This is made possible only by means of cutting edge image processing and recognition technology. Not satisfied? Facebook is currently working on applying the same technology to videos too. Once fully developed, the technology can detect the faces of the people known to the user from uploaded videos. Another example is the image search option provided by Google and certain online shopping platforms. This technology enables the user to search for a particular product by means of its image rather than the actual product name. Pretty cool, right?

Advertising:

Modern advertising is a great application of data science and assorted data analytics. Of late, advertisements have become target-specific. Advertisements are shown to the user based on past interests or on the search of related items. This has enabled many companies to prosper by making people want to buy products by means of user-intensive advertising. This is made possible from the application of advanced data science. Data science techniques are used to collect information from various users over varying periods of time. This data that is obtained is used for analysis further on. Based on the analyses, user-intensive recommendations are forwarded to the user. This phenomenon is known as target advertising. This is prevalent nowadays. Many online sellers and online shopping platforms have used target advertising to rake in a large number of customers. This has led to the meteoric rise of online businesses.

Online recommendations:

This digital age has seen widespread changes in even the smallest units of the internet. In order to meet the needs of the present and the future, almost everything has changed. This includes a change in our browsing patterns too. Everything on the web nowadays is recommended to the user based on his/her interest. This is again a direct result of advanced data science and analytics. Basically, recommendations are forwarded to a particular user based on the data collected regarding their usage of various online services. The times and patterns of the usage data are studied and recommendations are made. The YouTube algorithm is a great example for a recommendation making algorithms. It tries to make intelligent recommendations and, in its course, has become a host for various jokes relating to its complexity and randomness. Many websites are also recommended to users based on such data.

Gaming:

Gaming is one of the fields in which data science and other advancedtechnologies were used. Now the gaming industry has gained notoriety for being the house for cutting-edge science and data technologies. Games are only fun if they are made more competitive and more interesting than usual. This can be done using data science. Many new generation games use data collected from the user in a particular level to understand the user's level of playing to plan the progressive levels. This smarter system helps in making the game competitive without making it unplayable. Motion gaming is also another real time gaming application. In motion gaming, the computer attempts to learn the player's movements using a series of motion detection sensors. Using the player’s movements, the computer manages to up the ante and provide a stiffer competition to the gamer. Many prominent gaming companies are using these technologies for providing a better experience to customers.

Speech recognition and synthesis:

Speech synthesis and recognition is something that has amazed people over the years. Many forms of these technologies have existed over time. The past few years have seen a rise in the number of speech recognition software used like Google Voice, Microsoft Cortana and Apple Siri have gained prominence. These types of software generally can recognize a particular user's command and perform functions if connected to the internet. They are compatible with various mobile devices and affect people's daily lives. Another speech technology is speech synthesis. Text-to-speech synthesis is something that has never taken off. The technology involved in transforming written text into speech is very complicated. Until now, the proper transformation of text into speech without errors has not been made possible. A voice synthesizer will surely make a great gadget, directly from James Bond 007.

Risk detection:

Risk detection is a major field of interest for many management firms like banks and insurance companies. One of the earliest places where data science found this application was finance. Many finance companies and banks were tired of sanctioning unpaid loans and other frauds which caused them to lose money. So to cut costs, these companies decided to make dire decisions. As a result, they decided to employ data scientists to help them make even better decisions. This was due to the fact that banks had all sorts of data regarding customers, but were unable to contain frauds. Along with the help of the data scientists, banks were able to analyze data patterns and come up with better decisions. Needless to say, this scheme worked and banks were significantly able to reduce loss of money. As a result of this success, many companies began to use data science for better results.

Augmented reality:

One of the latest applications of data science is augmented reality. Many augmented reality games and apps have become the norm today. Such augmented reality apps and technologies collect real time data and are able to incorporate imagination with reality. Games like Pokémon Go, which was trending some time ago, is an excellent example of augmented reality games. The app employs the camera of the user's mobile device to capture real time data regarding the surroundings. Then the app projects the various game members, i.e. Pokémon at various locations for the user to literally 'catch' it. Many similar games and apps have also been developed. Augmented reality is surely the technology of the future. The ramifications of augmented reality being extended into various fields can lead to interesting consequences. From surgeries to construction, many technology firms have started employing augmented reality to meet with rapid prototyping demands.

Healthcare:

Data collected over time has been efficiently utilized by various hospitals. Previously collected data can be used for rapid diagnosis and providing immediate remedies to patients. Medical imaging recognition software is used to identify various diseases from imaging techniques like X-rays and MRI’s (Medical Resonance Imaging). This can help doctors in making better decisions and accelerate healing processes. Another use of data science is the development of various drugs and medicines. For the development of new compounds and medicines, thorough knowledge of existing chemicals is really important. This part of the job is undertaken by data scientists instead of doctors. This reduces the workload on doctors considerably.    

Future:

The future does present a lot of opportunities for data science and data scientists. Many high-end government and private scientists are tirelessly working on high- impact data science projects. The future of data science is very promising. As quoted by an eminent data scientist, “This is a great time to be a data scientist.”                          

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Author bio:

Senior Data Scientist and Alumnus of IIM- C (Indian Institute of Management - Kolkatta) with over 25 years professional experience ,Specialised in Data Science, Artificial Intelligence, and Machine Learning.

PMP Certified

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APMG, PEOPLE CERT and EXIN Accredited Trainer for all modules of ITIL till Expert

Trained over 3000+ professionals across the globe

Currently authoring book on ITIL "ITIL MADE EASY"

Conducted myriad Project management and ITIL Process consulting engagements in various organizations. Performed maturity assessment, gap analysis and Project management process definition and end to end implementation of Project management best practices.

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