[PDF] Top 20 Investigative Research on Big Data: An Analysis

... of data have bulk data that needs to be transformed, where the processing of each data item is essentially independent on the respective data items; that is, using a single-task and ... See full document

... of Big Data, it is a challenge for traditional data analysis and management ...no Data Description Language (DDL) and it supports transaction scale data is not universal and it ... See full document

... of research in which trillions of amounts are being spent by all ...using Big Data analytics with Evidence Based ...Patient analysis report is generated to monitor the recovery and patient ... See full document

... Big data is an evolving term that describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for ...information. Big data ... See full document

... where big data can make the greatest contribution. Research on network dynamics and the emergence of collective action from the co-evolution of structure and action has been filled with theoretical ... See full document

... the data is key for big data ...the big data ...in big data platform is still ...although big data technologies adoption is ...the big data ... See full document

... Big Data is one of the most excited and popular terms used in data analytics to describe a set of methodologies, techniques, and technologies which use new integration forms to uncover hidden ... See full document

... Abstract: Big Data is data that either is too large, grows too fast, or does not fit into traditional ...such data can be valuable information that can be discovered through data ... See full document

... on big data concepts and its handling ...Sentiment Analysis is a construct of Data Mining & ...handle big data and so its sentiment analysis with their pros & ... See full document

... Big data poses both opportunities and challenges for ...from big data, it must be processed and analyzed in a timely manner, and the results need to be available in such a way as to be able to ... See full document

... (GPUs) provide a vast number of simple, data-parallel, deeply multithreaded cores and high memory bandwidths. GPU architectures are becoming increasingly programmable, offering the potential for dramatic speedups ... See full document

... statistical analysis, but due to the increasing number of functions and packages, it has become popular in several fields, such as machine learning, visualization, and data ...all data (Big ... See full document

... of big data depends on the factors including people, technology and ...projects, big data requires different process approach which pertains to exploration and exploitation of data ... See full document

... for data-intensive tasks such as log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics ...Beyond data processing, ... See full document

... new data and other derivative works created from the exploitation of the licensed ...the data. Given all the complications of Big Data, it is of tantamount importance to a licensor that it ... See full document

... scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the ... See full document

... educational data-mining, the growing externalization of learning activity ...of data, in- cluding time spent on a resource, frequency of posting, number of logins, ...This data is fairly similar to ... See full document

... Contributions • Performance analysis of Big Data Tools • Time series data visualization • Parallel streaming algorithms • HPC integration to big data • Twister2 Big data toolkit.. • Unif[r] ... See full document

... from data, information, knowledge, meta-knowledge, to ...various analysis tasks, creating challenges for ...various analysis tasks and the quality of outcomes in ...in big Data ... See full document

... health data collected across millions of people, scientists can develop better algorithms for predicting future ...such data collection required specialized and inconvenient devices or a trip to the ... See full document