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Srivastava, Devesh Kumar
- Visualization Analytics for Big Data
Abstract Views :170 |
PDF Views:2
Authors
Affiliations
1 Manipal University Jaipur, School of Computing & Information Technology, Jaipur-303007, IN
1 Manipal University Jaipur, School of Computing & Information Technology, Jaipur-303007, IN
Source
Data Mining and Knowledge Engineering, Vol 7, No 3 (2015), Pagination: 111-116Abstract
This Paper presents the analysis technique which was operated on data sets refers to big data analytics and is classified as "Big Data". The next generation of data warehousing and business analytics is Big Data and is poised to deliver top line revenues cost efficiently for enterprises. Visualizing data is a technique to facilitate the identification of patterns in data and presenting data to make it more consumable. Charts, graphs, and dashboards have been used for decades to synthesize data into a cohesive and comprehensible format for business analysts, managers, and executives. These techniques have been used to differentiate the contexts and intents of the data to be visualized. Intents like Describing and Reporting. New techniques and tools are emerging that utilize exciting new visualization and animations to visually depict a story about data that far exceeds the standard charts, graphs, and dashboards. An evolving term, data artisans, describe people who create these new and dynamic visualizations.Keywords
Big Data, Big Data Analytics, Visualization, Business Analytics.- Reliability Modeling of a Cold Standby System with Different Repair Policies and Imperfect Coverage
Abstract Views :161 |
PDF Views:3
Authors
Affiliations
1 Department of Mathematics, Manipal University, Jaipur, IN
2 Department of Information Technology, Manipal University, Jaipur, IN
1 Department of Mathematics, Manipal University, Jaipur, IN
2 Department of Information Technology, Manipal University, Jaipur, IN
Source
Data Mining and Knowledge Engineering, Vol 6, No 8 (2014), Pagination: 327-331Abstract
This paper investigates a two-unit cold standby system with different repair policies and imperfect coverage. There is a single server remains always with the system to do repair, recovery and replacement of the unit after imperfect coverage. The failure time of the unit is exponentially distributed while the distribution of repair times, replacement time and recovery time of the unit follows arbitrary distribution. The unit works as new after repair and preventive maintenance. All random variables are statistically independent. Switch devices are perfect. By using semi-Markov process and regenerative point technique we analyse various performance measures of system effectiveness. The behaviour of some important measures of system effectiveness has been observed numerically with respect to repair rate by giving particular values to other parameters.Keywords
Reliability Modeling, Mean Time to System Failure (MTSF), Cold Standby System.- Big Challenges in Big Data Research
Abstract Views :226 |
PDF Views:3
Authors
Affiliations
1 Manipal University, Jaipur, IN
1 Manipal University, Jaipur, IN