APPLICATIONS OF BIG DATA

Big data applications solve and analyze real world problems using Hadoop and associated tools. Internet users and machine-to-machine connections are causing the data growth. Real time areas are defined following in which big data is used:

A. Big data in healthcare

Healthcare practices and policies differ tremendously around the world, there are three objectives regarding healthcare system [10]. The first objective is to improve the patient experience (including quality and satisfaction). Second, improving overall population health and reducing the cost of health care and third is traditional methods have fallen short to manage health care and create modern technology to analyze large quantities of information. It is time consuming for clinical staff to Collecting massive amounts of data in healthcare. High-performance analytics are new technologies making easier to turn massive amounts of data into relevant and critical insights used to provide better care. Analytics helps to predict negative intervene and reactions. Unstructured data can be captured through text mining from patient records. It means information can be collecting without causing additional work for clinicians. Transparent, information can thus improve encourage and quality innovation. A massive amount of data collected from different sources provides the best practices for today, and will help healthcare providers identify trends so they can achieve better results to improve medical facilities all around the world.

B. Network Security

Big data is changing the landscape of security technologies. The tremendous role of big data can be seen in network monitoring, forensics and SIEM [11]. Big data can also create a world where maintaining control over the revelation of our personal information is challenged constantly. Present analytical techniques don’t work well at large scales and end up producing false positives that their efficacy is undermined and enterprises move to cloud architectures and gather much more data, the problem is becoming worse. Big data analytics is an effective solution for processing of large scale information as security is major concern in enterprises. Fraud detection is uses for big data analytics. Phone and credit card companies have conducted large-scale fraud detection for decades. Mainly big data tools are particularly suited to become fundamental for forensics and ATP.

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C. Market and business

Big Data is the biggest game-changing opportunity for sales and marketing, since 20 years ago the Internet went main stream, because of the unprecedented array of insights into customer needs and behaviours it makes possible [12]. But many executives who agree that this is true aren’t sure how to make the most of it and they also find themselves faced with overwhelming amounts of data and rapidly changing customer behaviours, organizational complexity and increased competitive pressures. According to Gartner, 50% internet connection between Internet of things (IoT) devices and number reached over 15 billion in 2011 and 30 billion by 2020[18]. Some companies are succeeding at turning that Big Data promise into reality. Those that use Big Data and analytics effectively show profitability and productivity rates that are 5–6% higher than those of their peers. The companies that succeed aren’t the ones who have the most data, but the ones who use it best. Marketing of big data provides a strategic road map for executives who want to clear the chaos and start driving competitive advantage and top line growth. Using realworld examples additional downloadable resources, non-technical language, and a healthy dose of humour will help you discover the remedy offered by data-driven marketing. These insights to insure your business's  success.

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D. Sports

Sport, in business, an increasing volume of information is being collected and captured. Technological advances will fuel exponential growth in this area for the foreseeable future, as athletes are continuously monitored by tools as diverse as sports daily saliva, GPS systems and heart rate monitors tests. These statistics and many more like them are high performance in Big Data. These numbers there is a massive amount of potential insight and intelligence for trainers, administrators, coaches, athletes, sports medics and players. Statistics can be analyzed and collected to better understand what are the critical factors for optimum performance and success, in all facets of elite sport. Injury prevention, competition, Preparation, and rehabilitation can all benefit by applying this approach. Recruitment, Scouting and retention can also be enhanced by these powerful principles. Keeping an eye on various information a coach or a manager can easily and quickly understand which athletes and players need additional support, training, and guidance. Areas for reasons for success and improvement will be understood more clearly. Used consistently this is a powerful measure of progress and performance.

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E. Education Systems

By using big data analytics in field of education systems, remarkable results can be seen . Data on students online behaviour can provide educators with important insights, such as if a student requires more attention, the class understanding of a topic is not clear, or if the course has to be modified. Students are required to answer accompanying questions as they go through the set of online content before class. By tracking the number of students that have completed the online module, the time taken and accuracy of their answers, a lecturer can be better informed of the profile of his students and modify the lesson plan accordingly. The analysis of data also clarify about the interest of student looking at time spent in online textbook, online lectures, notes etc. As result instructor can guide choosing the future path effectively.

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F. Gaming industry

The amount of data that video game players are generating on a daily basis is growing rapidaitely. Video game developers are using variety of IT techniques such as Hadoop to keep up the massive amount of gamingdata that’s generated every day. People are playing video game and generated lot of data in separate areas: game data, player data and session data. In order to improve their game development, game experience, studios are turning to commercial Hadoop distributions such as MapR to analyze, collect and process data from these massive data streams. Armed with this valuable insight from big data, video game publishers are now able to enhance game player engagement and increase player retention by analyzing gamers’ social behaviour, activity and tracking players’ statistics, calculating rewards, quickly generating leader boards, changing game play and mechanics and delivering virtual prizes, so that experienced players will continue to play the game.Today big challenges for telecommunication are volume, variety and complexity. Current data systems based on batch processing and traditional relation technology, they process big data in real time. Telcos combine ETL and traditional relational databases with big data technologies on a single platform. Telcos technology parses, transforms and integrates the vast amount of data generated by location sensors, IPv6 devices, clickstream, CDRs, 4G networks and machine to machine monitors’ information. Cloud data integration helps to control over off-premise data managed in the cloud.

FUTURE SCOPE

The new applications are generating vast amount of data in structured and unstructured form. Big data is able to process and store that data and probably in more amounts in near future. Hopefully, Hadoop will get better. New technologies and tools that have ability to record, monitor measure and combine all kinds of data around us, are going to be introduced soon. We will need new technologies and tools for anonymzing data, analysis, tracking and auditing information, sharing and managing, our own personal data in future. So many aspects of life health, education, telecommunication, marketing, sports and business etc that manages big data world need to be polished in future.