DSAA 2017 - 4th IEEE International Conference on Data Science and Advanced Analytics 2017

Data driven scientific discovery approach has already been agreed to be
an important emerging paradigm for computing in areas including social,
service, Internet of Things (or sensor networks), and cloud. Under this
paradigm, Big Data is the core that drives new researches in many areas,
from environmental to social. There are many new scientific challenges
when facing this big data phenomenon, ranging from capture, creation,
storage, search, sharing, analysis, and visualization. The complication
here is not just the storage, I/O, query, and performance, but also the
integration across heterogeneous, interdependent complex data resources
for real-time decision-making, collaboration, and ultimately value
co-creation. Data sciences encompass the larger areas of data analytics,
machine learning and managing big data. Data analytics has become
essential to glean a deep understanding of large data sets and to
convert data into actionable intelligence. With the rapid growth in the
volumes of data available to enterprises, Government and on the web,
automated techniques for analyzing the data have become essential.