Artificial Intelligence (AI) is poised to revolutionize cellular networks, from right-sizing the network build to enhancing radio link performance and streamlining operations. One of the most significant impacts will be in optimizing network operations. By leveraging AI-powered solutions, operators can reduce costs, improve reliability, and monetize their data assets more effectively.

However, realizing the full potential of AI hinges on access to high-quality, sanitized, and verified data. Challenges such as data scarcity, lack of standardized formats, limited end-to-end visibility, privacy, security, and data sovereignty issues impede AI/ML model development and deployment. To address these obstacles, a comprehensive architecture is essential for collecting, analyzing, and curating data for AI/ML models.

This paper offers insights into:

• Role of AI in telecom networks

• Why valid data is critical for AIOps

• Four steps to holistic data management

Solving the data challenge of telecom AIOps

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