Abstract
Most efforts towards analyzing Big Data assume data parallel applications and handle the large volumes of data using Hadoop–like systems. However, Big Data is actually characterized by the 4V’s – Volume, Variety, Velocity and Veracity. We propose a Big Data Stack and analytics solution that particularly caters to this important problem of addressing Variety and Velocity aspects of data by exploiting inherent relationship among data elements. A unique approach that we propose to take is to integrate and model the data using non-planar graphs and discover new insights through sophisticated graph analytics techniques. We have integrated the stack with an intuitive visualization toolkit that enables focused exploration of data, through query and selective visualization - which will be demonstrated.
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Gupta, D., Sharma, A., Unny, N., Manjunath, G. (2014). Graphical Analysis and Visualization of Big Data in Business Domains. In: Srinivasa, S., Mehta, S. (eds) Big Data Analytics. BDA 2014. Lecture Notes in Computer Science, vol 8883. Springer, Cham. https://doi.org/10.1007/978-3-319-13820-6_4
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DOI: https://doi.org/10.1007/978-3-319-13820-6_4
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13819-0
Online ISBN: 978-3-319-13820-6
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