Plan Szkolenia
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
Wymagania
There are no specific requirements needed to attend this course.
Opinie uczestników (5)
I liked the virtual machine environments because he could easily toggle between the views and help if we were struggling with the material.
Pedro
Szkolenie - Apache NiFi for Developers
A lot of practical examples, different ways to approach the same problem, and sometimes not so obvious tricks how to improve the current solution
Rafał - Nordea
Szkolenie - Apache Spark MLlib
I liked that it was practical. Loved to apply the theoretical knowledge with practical examples.
Aurelia-Adriana - Allianz Services Romania
Szkolenie - Python and Spark for Big Data (PySpark)
how the trainor shows his knowledge in the subject he's teachign
john ernesto ii fernandez - Philippine AXA Life Insurance Corporation
Szkolenie - Data Vault: Building a Scalable Data Warehouse
This is one of the best hands-on with exercises programming courses I have ever taken.