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The Modern Data Architecture (MDA) project examines the latest requirements for upgrading data architecture in the telecoms industry. It delves into the technological advancements, shifts in telco business models, market dynamics, and environmental factors influencing telcos today to understand what distinguishes a modern architecture. By considering these factors, the project aims to define the characteristics that make an architecture “modern” in the current telecoms landscape.
This will be done through a focus on the following:
- Everyone wants data: The project is working to upgrade legacy architectures to ensure that collaboration on data can be effectively supported by Operators, and models can be shared, adapted and reused.
- There is more data: The project is providing the robust governance and policy enforcement mechanisms to ensure that data consumers only see the data for which they have permission to process.
- Data applications are more complicated: The project is defining the measures to be taken to enable data access whilst underpinning this with the appropriate data governance to minimize the risk of downstream application issues.
- Evolution: The autonomous operations goal of telcos: The project is enabling data management to be taken care of by the ‘machine’ itself, to realize the Zero-X, Self-X and Right-X efficiencies of an AI-enabled data architecture.
Project strategy:
The project is working to deliver a telco specific data reference architecture which enables telcos to not only run telecom networks but to effectively manage new business models.
Project FAQs
- Who should join?
Skills and experience are needed from those who want to get involved in collaboratively developing best practices and tools that enable placing data and AI at the core of operations.
- What commitment is required in terms of time and effort?
Provide commitment to join Wednesdays, 15:00 – 16:00 CET.
- What will I get out of this?
As a member of the Modern Data Architecture (MDA) project, you and your organization are able to contribute to and build the thought leadership, guide books, best practices and open standards that enable data productization, flexible business models, data operations efficiencies and effectiveness in managing the scale and complexity through the modernization of data architecture for AI-enabled telecom operations.
