Big Data in Telecom value chain. Presented by: Gurjot S Sandhu Director Sales Xalted Information Systems Pvt. Ltd.

Transcription

1 Big Data in Telecom value chain Presented by: Gurjot S Sandhu Director Sales Xalted Information Systems Pvt. Ltd.

2 Analyzing Big Picture

3 Big Data to CSPs

4 Traditional Analytics vs Big Data Approach Traditional Approach Analyze small subset of data Start with hypothesis and test against selected data Analyze data after it s been processed and landed in a warehouse Big Data Approach Analyze all data Explore all data and identify correlations Analyze data in motion as it s been generated, in real-time

5 Big Data in Telecom Value Chain (usage and non- Operational Intelligence Deeper understanding of switching, frequency utilization, Dynamic capacity profiling use to shall segment help in capacity customers by planning their: Customer SUBSCRIBER and management. USAGE behavior analysis REVENUE Historical v/s GENERIC INFORMATI Enhanced Customer Segmentation Mining Telecom machine data for Payments actionable DATA Present ON IN CDRs VoMS & Generic intelligence Usage (Website Mediation tracking information's, purchase CTOPUP System Data Billing Rating & Billing Geo-location history, based call center analysis data, response bandwidth to promotions, Customer HLR 360 VAS degree CDRs like Customer utilization Tables Profiling CUSTOMER IN etc) SMS, GPRS, MMS Plans, Package Customer Behavior Analytics CSPs can plan their expansions accordingly. MSDP MSDP, etc information ACCOUNT Optimizing Social cost of network Roaming, Facilities, usage) Social SMSC Media Monitoring telecom profiles tower maintenance NRTRDE CDRs Facebook, Vouchers, Twitter, OTA, etc Monitoring the speed (upload/download Prepaid Cards, LinkedIn, as defined Blogging, Location etc IMSIs in 3GPP/LTE) from various DATA LTE elements STREAM Predictive Churn Modeling Reconciliation Sentiment Socioeconomic between analysis the class data from probes, network logs, equipment vendors (network + 4G for Influence level in their cluster smartphone) Suspicious patterns xmeddy detection Access Big Data Metrics Propensity Report to Centralized churn Data for Senior Management to Real-time Fraud detection Realtime Processing Module ensure Drop optimal call Relationship usage analysis of the with infrastructure other TSPs users to provide Reporting best bandwidth Company s and Case to products the customer usability context M2M sensor data analysis for better products & identifications Managem Text mining Eg: on call Customer center transcripts in touch with Network Optimization services ent offering, optimized communication networks, prediction family and of adverse friends events while by roaming Module Relationships b/w factors analyzing leading to M2M churn sensor RAFMS System data Marketing, Price, Inventory Optimization WebClient Anywhere Copyright Xalted Information Systems. All Rights Reserved

6 Big Data Use case In customer life cycle Telcos which have predictive analytics embedded in all their business processes can abandon the decision making processes which are based on hit and trial methods or intuitions.

7 New and Over-the-Top / Adjacent Businesses Telecom can offer big data as a service to retail, hospitality and logistics customers. New product development This can helps in generating a better annual revenue for the Telcos. Analyzing customer behavior and transaction activities, important customer insights can be derived. TSPs can also leverage Machine 2 Machine (M2M) Expansion Into Vertical Markets operating models, in an effort to identify new business streams.

8 X a l t e d B I S o l u t i o n A R C H I T E C T U R E F R A M E W O R K Copyright Xalted Information Systems. All Rights Reserved

9 Unstructured Analytics: Key Features Real-time monitoring and surveillance of customer social activities Customizable Crawlers API s for Facebook, Twitter and other Social Media Platforms Text Analysis Network Infiltration and Engagement Geo Fencing iacuity 360 degree Profiling of customer Entity Extraction Co-relation with structured data sources Sentiment Analysis Case Management Discovery and exploration of linkages

10 Actionable Intelligence - iacuity Finding suspicious sites and messages Profiling people from information available on News, Twitter, Facebook, Blogs, Databases, Documents Evaluating sentiments in a location and projecting if potential threat for disruption exists Infiltrating a Suspect s Social Network Identifying persons of Interest Identify associates and acquaintances of person of interest Identify locations of criminals and criminal activity Gather evidences from Social Network Infiltrate Criminal Networks (Dark Web) Find out what, where and how Criminals are selling (Dark Web)

11 Data Analytics Intelius Platform

12 Lawful Interception: Voice, Video, Data Monitoring Xalted ilim is the solution for Monitoring and Analysis of Internet, Audio, Video, Data communications. The Xalted ilim solution is entirely projected and developed by Xalted for supporting the intelligence activities with solutions at the cutting edge of technology

13 Integrated of Voice, Data, Internet Analysis Relational Analysis Temporal Analysis Georeferential Analysis MobilePhone GSM-UMTS FAX LandLine POTS-ISDN SMS, MMS Communication WAP, GSM, GPRS VideoCalls 3G Internet Web2.0 VoIP, Mail, P2P, FTP, Chat Phone data VIDEO RECORDING

14 THANK YOU