Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can contain useful information
Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can contain useful information
We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-conidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental ...
In the data-driven world, business intelligence is in high demand. 97.2 percent of companies today are investing in big data and AI to drive growth and development.Despite this, many organizations face big data analytics challenges and strategic, tactical level efficiency. According to Gartner, 87...
In terms of computational efficiency, Big Data motivate the development of new computational infrastructure and data-storage methods. Optimization is often a tool, not a goal, to Big Data analysis. Such a paradigm change has led to significant progresses on developments of fast algorithms that are...
We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-conidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental ...
Thus, to trace the implementation of BD strategies, a profiling method is employed to analyze articles (published in English-speaking peer-reviewed journals between 1996 and 2015) extracted from the Scopus database. The analysis presented in this paper has identified relevant BD research studies ...
Big Da a analysis and compu a ion. In par icular, we emphasize on he viabili y o he sparses solu ion in high-confdence se and poin ou ha exogenous assump ions in mos s a is ical me hods or Big Da a canno be valida ed due o inciden al endogenei y. Tey can lead o wrong...
In the era of the fourth industrial revolution (Industry 4.0), big data has major impact on businesses, since the revolution of networks, platforms, people and digital technology have changed the determinants of firms' innovation and competitiveness. An ongoing huge hype for big data has been gai...
We are talking about “Hadoop”, a cost-effective and scalable platform for BigData analysis. Using the Hadoop system instead of Traditional ETL (extraction, transformation, and loading) processes gives you better results in less time. Running of Hadoop Cluster efficiently implies selecting an optima...