What if it were possible to empower communication service providers (CSPs) to reduce operational expenses and discover new revenue sources by automating mundane operations tasks and providing insights?
By examining three unique use cases, we will see how to leverage machine learning for prototyping advanced description, diagnostics, prescriptive and predictive analytics to deliver these aspirations.
- The first monitoring use case covers anomaly detection via ML and pattern recognition for adaptive and forecasting alerting systems. The aim is to predict KPI values based on historical values and other data.
- The second case explores SIM Box fraud detection. This helps CSPs with AI modeling to track users of SIM Boxes who try to by-pass termination fees, an illegal activity where mobile calls are prematurely terminated and routed instead to a local network cloud to avoid fees.
- The third use case focuses on the subscribers’ centres of interests, with the aim to understand these centres of interest via web traffic categorization. A solution can identify URLs browsed and then allocate them to more specific categories. This leads to new revenue streams (e.g., vendors working to buy the mobility profile data of a specific customer segment) and provide loyalty offers to increase net promoter scores.
Presenter: Anssi Tauriainen, Director – Data Science and Advanced Use Cases, EXFO
During the webinar, you'll learn:
- The galvanising effect of machine learning through 3 use cases
- Use case 1: Anomaly detection via ML and pattern recognition for clever, adaptive and forecasting alerting systems
- Use case 2: How to detect SIM Box fraud?
- Use case 3: Best route to subscriber centres of interests via web traffic categorization
Who should attend?
Industries: MNOs, Network and telecommunications companies, Digital Service Providers, Application and network performance providers and Big Data companies
Primary Roles: CTO, Head of OSS, Head of NFV / Virtualisation, Head of Service Assurance / performance management, Head of Network operations (NOC/SOC), Head of Core Networks, Head of Radio Networks, Head of customer experience, Chief Architect / Head of Enterprise Architecture and Head of Marketing
By exploring three unique use cases, we will highlight the prototyping of advanced descriptive, diagnostics, prescriptive and predictive analytics to empower CSPs.
Join SDxCentral and EXFO on September 5, 2018 at 10:00 am for Unlock the Value of Data Science: Machine Learning.
If you can't make it to the live event, register anyway. SDxCentral will let you know when the on-demand recording is available.
|Date:||Wednesday, September 5, 2018|
|Time:||10:00 am (PDT)|
|Title:||Unlock the Value of Data Science: Machine Learning|