Big Data: Methodological Challenges and Approaches for Sociological Analysis

Orchestrating Science DMZs for Big Data Acceleration: Challenges and Approaches

In recent years, most scientific research in both academia and industry has become increasingly data-driven. According to market estimates, spending related to supporting scientific dataintensive research is expected to increase to $5.8 billion by 2018 [1]. Particularly for dataintensive scientific fields such as bioscience, or particle physics within academic environments, data storage/process...

The Future of Big Data: Innovative Methodological Approaches.

Challenges of Big Data Analysis.

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability a...

Big data analysis: Trends & challenges

Big data is a popular term for describing the exponential growth, availability and use of information, both structured and unstructured. Much has been written on the big data trend and its potentiality for innovation and growth of enterprises. The advise of IDC (one of the premier advisory firm specialized in information technology) for organizations and IT leaders is to focus on the ever-incre...

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex hea...