MDAS

Management Data Analytics Service

Management →
Introduced in Rel-15 Also in: Services

MDAS is a service-based capability that provides analytics on network management data, exposing functions like the MDAF to authorized consumers for optimization, fault management, and performance assurance.

Category
Management
Introduced
Rel-15
Where
Management
Also touches
1 segments
Specifications
11 specs
MDAS Description Purpose Related Classification Detected Changes Specifications

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).

Classification

Part ofMDAF
Related approachesOSS

Release Timeline

Detected Changes Across Releases

from 3GPP Change Requests

Specific changes extracted from the „Change history“ tables of 3GPP specifications (1 CRs across 1 releases). Complements the general historical overview above with the evidence-based evolution of this function.

Studied in Rel-15, normative work from Rel-18.

Rel-18 1 change

In Release 18, a correction was made to the Management Data Analytics Service (MDAS) function to clarify its role in providing analytics to consumers like the VAL server or SEAL NSCE. The update specifies that MDAS can provide analytics based on data from sources such as OAM, EAS/ASP for computational load, N6 endpoints, 5GC/NWDAF, and MEC platform services. This includes analytics on EAS load, N6 load, DN performance, and UPF load per DNAI.

  • Rel-18 CR 28.533 Correct A.5 Management Data Analytics Service (MDAS) TS 28.533CR0139

Explore further

Broader topics and technologies where MDAS plays a role.

Defining Specifications

3GPP specifications that define or reference MDAS, with the latest known release. Sourced from the 3GPP document catalog — see methodology.

SpecificationTitleRelease
TS 23.436 vk00 ADAEnabler Functional Architecture and Information Flows Rel-20
TS 23.700 vk00 XR Services Application Enablement Layer Rel-20
TS 28.104 vj30 Management Data Analytics (MDA) Rel-19
TS 28.533 vj30 Management and orchestration; Architecture framework Rel-19
TS 28.535 vj00 Closed Control Loop Assurance Management Rel-19
TS 28.536 vj20 Management services for communication service assurance Rel-19
TR 28.809 vh00 Enhancement of Management Data Analytics (MDA) Study Rel-17
TS 28.866 vj00 Study on Management Data Analytics (MDA) – Phase 3 Rel-19
TS 28.890 vg00 ONAP-3GPP 5G Management Compatibility Study Rel-16
TS 32.240 vj40 Charging Management Architecture & Principles Rel-19
TR 33.866 vh00 Security aspects of Network Automation enablers for 5GS Rel-17
Patrick Zandl

About the author: Patrick Zandl (b. 1974)

Telecommunications specialist, technology journalist (founder of the Mobil server), and developer who has been running since 2025 — the largest Czech-language resource on AI-assisted programming. Formerly Chief Wizard Architect at Prusa3D and head of development for Turris at CZ.NIC; currently a consultant and instructor on AI implementation in companies.