Management Data Analytics Service

Description

The Management Data Analytics Service (MDAS) is a conceptual service layer that represents the exposure of management data analytics capabilities in a 3GPP system. Introduced in Release 15, it is not a standalone network function but rather the service interface and capability set through which analytics are consumed. The primary provider of this service is the Management Data Analytics Function (MDAF), introduced later. MDAS defines how consumers, which can be other management functions (e.g., Network Slice Management Function), network functions, or operations support system (OSS) applications, can interact with analytics producers.

The service is defined by a set of service operations, data models, and information models standardized in 3GPP specifications. Key operations include subscribing to an analytics stream, requesting an on-demand analytics report, and managing analytics subscriptions. The service handles the negotiation of analytics types, input data requirements, and output formats. It works through a producer-consumer model where the producer (e.g., MDAF) advertises its available analytics capabilities, and the consumer discovers and invokes them. The data exchanged includes analytics input (like performance measurement data or fault alerts) and analytics output (like predictions, recommendations, or identified anomalies).

Architecturally, MDAS is realized through service-based interfaces (SBIs) within the 5G core network's management framework. It ensures interoperability between different vendors' analytics solutions and management systems. The service covers a broad scope of analytics, including performance analytics (e.g., predicting Key Performance Indicator degradation), fault analytics (e.g., root cause analysis), and configuration analytics (e.g., optimization recommendations). Its role is to decouple the analytics logic implementation from the consumers, providing a standardized, reusable, and scalable way to inject intelligence into network management and orchestration workflows.

Purpose & Motivation

MDAS was created to establish a standardized, flexible, and open framework for consuming analytics within the 3GPP management ecosystem. Before its definition, management systems relied on proprietary interfaces and embedded analytics, making it difficult to integrate best-of-breed analytics solutions or to share insights across different management domains. This siloed approach hindered automated and coordinated network management.

The purpose of MDAS is to solve this integration challenge by defining a common service layer. It allows network operators to procure analytics capabilities from different vendors and have them seamlessly consumed by their existing OSS and management functions. This promotes innovation and competition in the analytics market. Furthermore, it supports the 5G vision of network automation by providing a clear mechanism for management functions to obtain the data-driven insights necessary for autonomous decisions, such as dynamically adjusting network slice resources or pre-emptively addressing congestion.

Historically, management systems were moving towards more data-driven operations, but lacked a unified model. MDAS, along with the later MDAF, provides this model. It addresses the limitation of previous ad-hoc integrations by offering a future-proof, service-oriented architecture for analytics consumption, which is essential for managing the complexity of 5G networks and enabling advanced use cases like zero-touch network and service management (ZSM).

Key Features

• Standardized service operations for analytics subscription and request
• Support for multiple analytics types (performance, fault, configuration, etc.)
• Discovery mechanism for available analytics capabilities
• Flexible data models for analytics input and output
• Enabler for vendor-agnostic integration of analytics into management systems
• Foundation for intent-based management and closed-loop operations

Evolution Across Releases

Defining Specifications