Database Reference
In-Depth Information
only correct data should be utilized, but also the wrong data should be utilized to
generate more value. Collecting and analyzing data exhaust can provide valuable
insight into the purchasing habits of consumers.
7.1.3
Practical Implications
Although there are already many successful big data applications, many practical
problems should be solved:
Big Data Management
: the emergence of big data brings about new challenges to
traditional data management. At present, many research efforts are being made
on consider big data oriented database and Internet technologies, management
of storage models and databases of new hardware, heterogeneous and multi-
structured data integration, data management of mobile and pervasive computing,
data management of SNS, and distributed data management.
Searching, Mining, and Analysis of Big Data
: data processing is always a
research hotspot in the big data field, e.g., searching and mining of SNS models,
big data searching algorithms, distributed searching, P2P searching, visualized
analysis of big data, massive recommendation systems, social media systems,
real-time big data mining, image mining, text mining, semantic mining, multi-
structured data mining, and machine learning, etc.
Integration and Provenance of Big Data
: As discussed, the value acquired from
a comprehensive utilization of multiple datasets is higher than the total value
of individual datasets. Therefore, the integration of different data sources is a
timely problem to be solved. Data integration is to integrate different datasets
from different sources, which are confronted with many challenges, such as
different data patterns and large amount of redundant data. Data provenance is to
describe the process of data generation and evolution over time. In the big data
era, data provenance is mainly used to investigate multiple datasets other than a
single dataset. Therefore, it is worth of study on how to integrate data provenance
information featuring different standards and from different datasets.
Big Data Application
: at present, the application of big data is just beginning and
we shall explore and more efficiently ways to fully utilize big data. Therefore, big
data applications in science, engineering, medicine, medical care, finance, busi-
ness, law enforcement, education, transportation, retail, and telecommunication,
big data applications in small and medium-sized businesses, big data applications
in government departments, big data services, and human-computer interaction
of big data, etc. are all important research problems.
7.1.4
Data Security
In IT, safety and privacy are always two key concerns. In the big data era, as data
volume is fast growing, there are more severe safety risks, while the traditional data
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