Open Issues and Outlook - Big Data: Related Technologies, Challenges and Future Prospects - page 79

Chapter 7
Open Issues and Outlook

Abstract In the previous chapters, we review the background and state-of-the-art
of big data. In Fig. 7.1 , it illustrates all the key technologies of big data introduced in
this topic. In this chapter, we summarize the research hot spots and suggest possible
research directions of big data. We also discuss potential development trends in this
broad research and application area.

7.1 Open Issues

The analysis of big data is confronted with many challenges but the current research
is still in the beginning phase. Considerable research efforts are needed to improve
the efficiency of data display, data storage, and data analysis.

7.1.1 Theoretical Research

Although big data is a hot research area in both academia and industry, there are
many important problems remain to be solved, which are discussed below.

￿ Fundamental Problems : There is compelling need for a rigorous definition of

big data, a structural model of big data, formal description of big data, and a
theoretical system of data science, etc. At present, many discussions of big data
look more like commercial speculation than scientific research. This is because
big data is not formally and structurally defined and not strictly verified.

￿ Standardization : An evaluation system of data quality and an evaluation standard

of data computing efficiency should be developed. Many solutions of big data
applications claim they can improve data processing and analysis capacities in
all aspects, but there is still not a unified evaluation standard and benchmark
to balance the computing efficiency of big data with rigorous mathematical