scope:

The present document describes some technical methods to support data-driven intelligent network scenarios. The realization of intelligent networks depend on extracting value from Big Data using AI algorithms. Therefore, effective data acquisition, processing and management is extremely important as described in this context.

The present document covers the following aspects:

1) Data classification in terms of the data sources producing the data (e.g. network management system, network elements, servers, terminals and external environment data), data characteristics (e.g. configuration or sequential data), and data format.

2) Data operation including data collection, data storage, data processing, data sharing and data management:

a) Data collection including description about collection modes (e.g. pull (query/request response) and push (publish/notify)), and data collection techniques, such as telemetry.

b) Data storage recommendations.

c) Data processing, including data cleansing and data correlation.

d) Data sharing.

e) Data management, including metadata management, data security management and data quality management.

3) Data acquisition and processing methods of selected use cases proposed in ETSI GR ENI 001 [i.1] for ENI systems executing intelligent tasks.