Page 27 - Big data - Concept and application for telecommunications

Big data - Concept and application for telecommunications 1

9 Cloud computing based big data capabilities

9.1 Data collection capabilities
Data collection capabilities include:

– Data source intelligent recognition, which offers the capabilities to locate the data sources and
detect the types of data being collected;
– Data adaptation, which offers the capabilities to transform and organize the data being collected
with targeted data structures and attributes (numbering, location, ownerships, etc.);
– Data integration, which offers the capabilities to integrate data from different data sources
(different data types) using metadata or ontology;
– Data brokerage, which offers the capabilities to provide a brokerage service for searching data.

9.2 Data pre-processing capabilities

Data pre-processing capabilities include:
– Data extraction, which offers the capabilities to extract information from the semi-structured data
or unstructured data;
– Data transmission, which offers the capabilities to transport datasets (static data and real-time data)
from data sources or between one location to another keeping the integrity and consistency;

– Data de-noising, which offers the capabilities to eliminate noise information from a mixture of signal
data and noise data;
– Data aggregation, which offers the capabilities to aggregate data which come from different sources
in the same data model or data format.

9.3 Data storage capabilities

Data storage capabilities include:
– Data storing, which offers the capabilities to store different types and formats of data with elastic
storage capacity;
– Data registration, which offers the capabilities to create, update and delete the metadata with
corresponding changes in data storage;
NOTE – In the case of unstructured data registration, the data registration component can request
the transforming of raw data to semi-structured data such as JavaScript object notation (JSON) or
binary JavaScript object notation (BSON) to define semantic relationships among different datasets
for knowledge sharing.
– Data access, which offers the capabilities to access data through multiple interfaces, such as web
service interfaces, file system interfaces, database interfaces and so on;
– Data indexing, which offers the capabilities to create and update indexes for datasets;
– Data duplication and backup, which offers the capabilities to duplicate and make backups for
datasets.

9.4 Data analytics capabilities
Data analytics capabilities include:

– Data preparation, which offers the capabilities to transform data into a form that can be analysed.
These capabilities include exploring, changing and shaping of the raw data;

– Data analysis, which offers the capabilities of investigation, inspection and modelling of data in order
to discover useful information;
– Workflow automation, which offers the automation processes, in whole or part, during which data
or functions are passed from one step to another for actions, according to a set of procedural rules;

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