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
Detected Changes Across Releases
from 3GPP Change RequestsSpecific changes extracted from the „Change history“ tables of 3GPP specifications (81 CRs across 6 releases). Complements the general historical overview above with the evidence-based evolution of this function.
In Release 15, the MDAS (Management Data Analytics Service) was newly introduced to provide a framework for application data analytics enablement. This included defining an ADAE server capable of collecting data from diverse OAM, 5GC, and UE sources, storing analytics in an Application layer Analytics and Data Repository Function (A-ADRF), and exposing edge data analytics to VAL applications. The architecture also introduced service-based interfaces, such as SAdae, and integrated support for consuming AIML-enabled services to enhance its analytics capabilities.
In Release 16, the MDAS function was enhanced by formally defining its deployment based on the ZSM framework and adding new management capabilities for multi-tenant environments. It introduced explicit coordination with the NWDAF for consuming network analytics and added an annex detailing state management procedures. Furthermore, the overall management service description and architectural diagrams were updated to reflect these new integrations and deployment models.
- Add 3GPP Management Service deployment based on ZSM Framework TS 28.533CR0028
- Add description for management capability support in multiple tenant environment TS 28.533CR0044
- Update Clause 5.3 Management service deployment based on ZSM framework TS 28.533CR0057
- Add Annex on state management TS 28.536CR0013
- Add management coordination with NWDAF TS 28.533CR0031
- Update of Management service description and diagram TS 28.533CR0039
+ 1 more changes
In Release 17, the Management Data Analytics Service (MDAS) saw refinements including corrections to the analytics window definition and the management data analytics capability description. Updates were made to the description of management control loops to incorporate their lifecycle, and the charging architecture for the management domain was corrected. Furthermore, the specification removed redundant monitoring content and unnecessary stage 2 details for the discovery of management services.
- Remove unnecessary stage 2 details for discovery of management services TS 28.533CR0086
- Correction of definition for analytics window TS 28.104CR0025
- Remove S-NSSAI from example of analytics output TS 28.104CR0026
- Delete redundant monitoring content of the management system TS 28.535CR0069
- Correct the Management Data Analytics Capability Description TS 28.533CR0102
- Update management control loops with lifecycle description TS 28.535CR0049
+ 1 more changes
In Release 18, the Management Data Analytics Service (MDAS) introduced new analytics procedures and enhanced capabilities, specifically for application performance, edge load, and location accuracy. This included new support for slice-specific, UE-to-UE, and service API analytics, as well as enhanced edge performance analytics to cover transmission quality. The updates also provided clarifications on analytics request parameters and further integrated the service within the broader Application Data Analytics Enablement (ADAE) architecture.
- Update MDA capability of fault management for interruption scenario TS 28.104CR0056
- CR TS 28.104 Rel-18 eMDAS_Ph2 Further enhancements into the Management Data Analytics (Phase 2) TS 28.104CR0090
- Add example of RAN domain management capabilities mapped with ZSM TS 28.533CR0120
- Using Management Services to support multiple players interoperability TS 28.533CR0121
- Rel-18 CR TS 28.533 Update Annex F Usage of CRUD operations and NRM fragments to support management capabilities in SBMA TS 28.533CR0124
- Extend the edge performance analytics to support transmission quality analytics TS 23.436CR0004
+ 24 more changes
In Release 19, the MDAS function was expanded with new analytics capabilities including collision detection, location-related UE group analytics, and support for application layer AI/ML member capability analytics. It also introduced analytics for non-terrestrial access UE RAT connectivity, VAL performance for tethered UEs, and DN energy analytics. Furthermore, the release added comprehensive support for management data correlation analytics, specifically for use cases like threshold assessment/adjustment and NF scaling/dimensioning.
- Edge computing preparation analytics TS 23.436CR0030
- Support of Collision Detection Analytics TS 23.436CR0037
- Support of Location-related UE Group Analytics TS 23.436CR0038
- Support of Application Layer AI/ML Member capability Analytics TS 23.436CR0039
- UE RAT connectivity analytics for non terrestrial access TS 23.436CR0040
- Support for VAL performance analytics for tethered UEs TS 23.436CR0044
+ 28 more changes
In Release 20, the MDAS function, specifically within the Application Data Analytics Enablement Service (ADAES), introduced new support for monitoring the correctness of ML-enabled analytics. This was enabled through an enhanced architecture where the ADAES can consume services from an AIML Enabler (AIMLE) server via the new AIML-X interface for operations like ML model training. This allows the ADAES to provide enhanced, ML-driven analytics for vertical applications, such as VAL server performance or UE location accuracy, based on trained models.
- Support monitoring ML-enabled analytics correctness TS 23.436CR0064
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.
| Specification | Title | Release |
|---|---|---|
| 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 |