Big Data Analytics for Telecom Regulators培训

课程编码

BDATR

课程时长

14 小时 通常来说是2天,包括中间休息。

要求

There are no specific requirements needed to attend this course.

课程概览

为了满足监管机构的合规要求,CSP( Communication服务提供商)可以利用大数据分析,这不仅可以帮助他们满足合规性,而且在同一项目的范围内,他们可以提高客户满意度,从而减少客户流失。事实上,由于合规性与合同相关的服务质量有关,因此任何实现合规性的举措都将提高CSP的“竞争优势”。因此,监管机构应该能够为监管机构和CSP之间互利的CSP建议/指导一套Big Data分析实践,这一点非常重要。

该课程包括8个模块(第1天4个,第2天4个)

Machine Translated

课程大纲

1. Module-1 : Case studies of how Telecom Regulators have used Big Data Analytics for imposing compliance :

  • TRAI ( Telecom Regulatory Authority of India)
  • Turkish Telecom regulator : Telekomünikasyon Kurumu
  • FCC -Federal Communication Commission
  • BTRC – Bangladesh Telecommunication Regulatory Authority

2. Module-2 : Reviewing Millions of contract between CSPs and its users using unstructured Big data analytics

  • Elements of NLP ( Natural Language Processing )
  • Extracting SLA ( service level agreements ) from millions of Contracts
  • Some of the known open source and licensed tool for Contract analysis ( eBravia, IBM Watson, KIRA)
  • Automatic discovery of contract and conflict from Unstructured data analysis

3. Module -3 : Extracting Structured information from unstructured Customer Contract and map them to Quality of Service obtained from IPDR data & Crowd Sourced app data. Metric for Compliance. Automatic detection of compliance violations.

4. Module- 4 : USING app approach to collect compliance and QoS data- release a free regulatory mobile app to the users to track & Analyze automatically. In this approach regulatory authority will be releasing free app and distribute among the users-and the app will be collecting data on QoS/Spams etc and report it back in analytic dashboard form :

  • Intelligent spam detection engine (for SMS only) to assist the subscriber in reporting
  • Crowdsourcing of data about offending messages and calls to speed up detection of unregistered telemarketers
  • Updates about action taken on complaints within the App
  • Automatic reporting of voice call quality ( call drop, one way connection) for those who will have the regulatory app installed
  • Automatic reporting of Data Speed

5. Module-5 : Processing of regulatory app data for automatic alarm system generation (alarms will be generated and emailed/sms to stake holders automatically) :
Implementation of dashboard and alarm service

  • Microsoft Azure based dashboard and SNS alarm service
  • AWS Lambda Service based Dashboard and alarming
  • AWS/Microsoft Analytic suite to crunch the data for Alarm generation
  • Alarm generation rules

6. Module-6 : Use IPDR data for QoS and Compliance-IPDR Big data analytics:

  • Metered billing by service and subscriber usage
  • Network capacity analysis and planning
  • Edge resource management
  • Network inventory and asset management
  • Service-level objective (SLO) monitoring for business services
  • Quality of experience (QOE) monitoring
  • Call Drops
  • Service optimization and product development analytics

7. Module-7 : Customer Service Experience & Big Data approach to CSP CRM :

  • Compliance on Refund policies
  • Subscription fees
  • Meeting SLA and Subscription discount
  • Automatic detection of not meeting SLAs

8. Module-8 : Big Data ETL for integrating different QoS data source and combine to a single dashboard alarm based analytics:

  • Using a PAAS Cloud like AWS Lambda, Microsoft Azure
  • Using a Hybrid cloud approach

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