Indian Journal of Science and Technology
Year: 2017, Volume: 10, Issue: 42, Pages: 1-7
S. Sanila1 , D. Venkata Subramanian2 and S.Sathyalakshmi2
1Department of CSE, Hindustan University, Padur, Kelambakam − 603103, Chennai, Tamil Nadu, India; [email protected] 2School of Computing Sciences, Hindustan University, Padur, Kelambakam − 603103, Chennai, Tamil Nadu, India; [email protected], [email protected]
Background/Objectives: Big Data refers to a set of data that is too big to be managed without using new algorithmic technologies. It is a term used to describe datasets of huge sizes that cannot be handled with the typical data mining software tools. It is critical in today’s modern, agile and ever changing environment for systems to extract useful information from data in real-time. Data warehouses are valuable sources of information, but their value becomes enhanced multifold when information is collected and analyzed on the go. Real- Time data analytics are techniques which involves the evaluation of streaming data. Methods: Real-Time analytics will enable visualization of the changes as and when they happen. The development of technologies and the deployment of new generation applications influenced the social environment. One side it is tempting the whole nation to development and the other side it is affecting social bonding and responsible attitude of the youth. Any application area becomes “smart” when it is highly advanced in terms of overall infrastructure, sustainable energy and communication mechanisms which will provide essential services to providers. Findings: Mining from these real-time data is interesting and extremely challenging as all the predictions, classifications and complicated analysis have to be done on the go itself. Improvements and Applications: The in-depth analysis of the existing technologies needs to be carried out thoroughly and its applications have to be modified accordingly.
Keywords: Cloud Computing, Hadoop-Map Reduce, Real-Time Data Analytics, Smart Applications, Spark, Stream Processing
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