Page 23 - Big data - Concept and application for telecommunications

Big data - Concept and application for telecommunications 1

7.1.3.2 Perform data storage activity

The perform data storage activity allows storing of the data collected and the pre-processing results using
storage resources and building of corresponding databases to manage and manipulate the data.
7.1.3.3 Provide data pre-processing activity
The provide data pre-processing activity realizes extraction, transformation and de-noising of the collected
data. Since there are many different data formats and data types of the collected data, the transformation
and extraction of complex data into simple structured data facilitates and speeds up the data analysis
process.

The data de-noising process filters out the defects in data to eliminate negative effects in the normal analysis
process.
7.1.3.4 Provide data integration activity
The provide data integration activity is responsible for combining, forming, coordinating or blending data
from disparate sources and for solving the issues of bulk data movement, replication, synchronization,
virtualization, data quality and data services.
7.1.3.5 Manage data protection activity
The manage data protection activity is responsible for protecting data so that the protected data may not be
collected, stored and disclosed to whom may not be appropriate.

7.1.3.6 Manage data provenance activity
The manage data provenance activity manages information about the origin and generation process methods
of data. Such information is useful for debugging, transformations, auditing, evaluating the quality of and
trust in data, modelling authenticity and implementing access control for derived data.

7.1.4 CSC:big data service user (CSC:BDSU)
CSC:big data service user (CSC:BDSU) is the sub-role of the CSC performed by end-users or other systems in
order to use the services from the CSP:BDAP and CSP:BDIP.
Types of CSC:BDSU activities include:

– use big data service;
7.1.4.1 Use big data service
The use big data service involves using the services of a CSP:BDAP and a CSP:BDIP in order to accomplish
tasks.
Use big data service activity typically involves:

– provision of user credentials to enable the CSP:BDAP and CSP:BDIP to authenticate the user and
grant access to the big data service;

– invocation of the big data service.

7.2 Benefits of cloud computing based big data
One of the main purposes of big data is to extract deep information from large volumes of data. Large
volumes of data can be analysed using two key methods; the scale-up method and the scale-out method.
The scale-up method uses a large system with enough resources to analyse a huge amount of data. In
contrast, the scale-out method uses many separate processing nodes, where each processing node analyses
a portion of data. The scale-out method has the ability to scale just by adding more processing nodes. Cloud
computing can provide big data with cost-effective elastic processing, storage and network resources.
The key benefits of cloud computing based big data are:
– Scalability. Big data needs to have capabilities to store and process large volumes of data. Therefore,
scalability is very important for big data. However, the additional systems for big data require a lot
of time and cost management. Cloud computing can provide flexible scalabilities to big data without

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