Page 25 - Big data - Concept and application for telecommunications

Big data - Concept and application for telecommunications 1

4) It is recommended for the CSP:BDIP to support extraction of data from unstructured data or semi-
structured data into structured data.
NOTE – This requirement can be applied also to data storage.

8.3 Data storage requirements

The data storage requirements include:
1) It is required for the CSP:BDIP to support different data types with sufficient storage space, elastic
storage capacity and efficient control methods;
2) It is required for the CSP:BDIP to support storage for different data formats and data models;
NOTE – Data formats include text, spreadsheet, video, audio, image, map, etc. Data models include
relational models, document models, key-value models, graph models, etc. (as described in
clause 6.1).

3) It is required that the CSP:BDIP provides a flexible licensing policy for the databases;
NOTE – As database systems may be covered by vendor licenses, the CSP:BDIP that offers a database
as part of the big data service needs the ability to adapt the licensing conditions to the particular
service and the CSC:BDSU requirements.
4) It is recommended that the CSP:BDIP provides different types of databases;

NOTE – Examples of database types include relational databases (RDB), object relational databases
(ORDB), object oriented databases (OODB), NoSql (not only SQL) databases, etc.
5) It is recommended for the CSN:DP to expose application programming interfaces (APIs) for data
delivery;
6) It is recommended that the CSP:BDIP fulfils storage and database performance demands.
7) It is recommended that the CSP:BDIP supports a data retention policy covering a data retention
period before its destruction after termination of a contract. This is to protect the big data service
customer from losing private data through an accidental lapse of the contract.

8.4 Data analysis requirements

The data analysis requirements include:
1) It is required for the CSP:BDAP to support analysis of various data types and formats;
2) It is required for the CSP:BDAP to support batch processing;
3) It is required for the CSP:BDAP to support association analysis;
NOTE – Association analysis is the task of uncovering relationships among data.
4) It is required for the CSP:BDAP to support different data analysis algorithms;

NOTE – Data analysis algorithms include classification, clustering, regression, association, ranking,
etc.
5) It is required that the CSP:BDAP provides flexible licensing policy for the analytical applications;

6) It is recommended for the CSP:BDAP to support user defined algorithms;
7) It is recommended for the CSP:BDAP to support data processing in distributed computing
environments;
8) It is recommended for the CSP:BDAP to support data indexing;
9) It is recommended that the CSP:BDAP supports data classification in parallel;
10) It is recommended that the CSP:BDAP provides different analytical applications;
11) It is recommended that the CSP:BDAP supports customization of analytical applications;

12) It is recommended for the CSP:BDAP to support real-time analysis of streaming data;
13) It is recommended for the CSP:BDAP to support user behaviour analysis;

Basics of Big data 17