Modernising CSPs’ data architectures for network analytics/AI-driven automation

11 October 2023 | Research

Adaora Okeleke

Strategy report | PPTX and PDF (17 slides) | AI and Data Platforms


"CSPs that do not act now to transform data architectures to enable network analytics/AI-driven automation by using modern best practices, will limit how quickly they meet their autonomous networking goals."

AI_network-735x70x1212064060.jpg

Communications service providers (CSPs) are defining their strategies for autonomous networks. Current data architectures will fail to support these strategies. CSPs must transform data architectures using modern best practices to create a framework that eases the creation and exposure of network insights for automation.

Information included in this report

  • Analysis of the market factors and challenges motivating CSPs to transform data architectures for network analytics/AI-driven automation
  • A summary of the best practices recommended for CSPs in the development of new data architectures that facilitate network analytics/AI-driven automation
  • Insights into how CSPs are currently implementing these best practices and leveraging cutting-edge technologies to transform data architectures in support of network analytics/AI-driven automation

USD4999

Log in

Log in to check if this content is included in your content subscription.

Author

Adaora Okeleke

Principal Analyst, expert in AI and data management