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Big Data Analytics use Big Data Analytics use Big Data Analytics use Big Data Analytics use cases cases cases cases Zhao Lifen China Mobile

Big Data Analytics use casescrc.gov.mn/file/newfile/TMW21543 L_ZAHO_FINAL.pdf · Big Data Analytics use casesBig Data Analytics use cases Zhao Lifen ... Analysis PI Network Element

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Big Data Analytics use Big Data Analytics use Big Data Analytics use Big Data Analytics use casescasescasescases

Zhao Lifen

China Mobile

Which areas offer the most promising opportunities for big data and analytics?

Opportunities for big data and analytics

Source: Managing and mining big data (TMF Insight research)

Value of Big Data for CSP

� Improve Customer ExperienceImprove Customer ExperienceImprove Customer ExperienceImprove Customer Experience

� Assist Marketing DecisionsAssist Marketing DecisionsAssist Marketing DecisionsAssist Marketing Decisions � Optimize Network PerformanceOptimize Network PerformanceOptimize Network PerformanceOptimize Network Performance

requirements

Traffic Traffic Traffic Traffic AAAAnalysisnalysisnalysisnalysis

Customer Customer Customer Customer AnalysisAnalysisAnalysisAnalysis

Revenue Revenue Revenue Revenue ManagementManagementManagementManagement

Network Quality and Performance

Analysis

Network Value Analysis

End-to-End Analysis of Service

Customer Behavior Analysis

PINetwork Element Layer

KPINetwork Performance Layer

KQIService quality layer

QOECustomer Perception Layer

CSP should extract value of big CSP should extract value of big CSP should extract value of big CSP should extract value of big

data based on cloud computing data based on cloud computing data based on cloud computing data based on cloud computing

technology and advantages of CSP. technology and advantages of CSP. technology and advantages of CSP. technology and advantages of CSP.

For China Mobile, the following For China Mobile, the following For China Mobile, the following For China Mobile, the following

are our priorities.are our priorities.are our priorities.are our priorities.

Use Case1:Improve

Customer Experience—query

of bill and detailed record

Implementation Architecture

CDR process CDR query� Process CDR queries from Process CDR queries from Process CDR queries from Process CDR queries from all channels, all channels, all channels, all channels,

portalportalportalportal, , , , customer service customer service customer service customer service hhhhotline, selfotline, selfotline, selfotline, self----

service terminals, etc.service terminals, etc.service terminals, etc.service terminals, etc.

� Traditional solution: UNIX server +disk Traditional solution: UNIX server +disk Traditional solution: UNIX server +disk Traditional solution: UNIX server +disk

array,array,array,array,--------High costHigh costHigh costHigh cost,,,,difficult scaledifficult scaledifficult scaledifficult scale----

out,lowout,lowout,lowout,low performance when heavy loadperformance when heavy loadperformance when heavy loadperformance when heavy load,,,,etc.etc.etc.etc.

� Based on HadoopBased on HadoopBased on HadoopBased on Hadoop and and and and HbaseHbaseHbaseHbase, the system , the system , the system , the system

architecture can:architecture can:architecture can:architecture can:

• HighHighHighHigh----efficiency queryefficiency queryefficiency queryefficiency query

• ScaleScaleScaleScale----out easilyout easilyout easilyout easily

• Agile statisticsAgile statisticsAgile statisticsAgile statistics

Use Case2: Assist Marketing Decisions

— customer tags

SGSN

BTS/NodeB

eNodeB

BSC/RNC

GGSN/SAE-GW

GatewayGn

DPI① Interface: Gn

AC

③ Location infoMSC

BTS BSC

Interface: A

BillingSystem

Big Data Analytics System

Billing CDR

CG

Accurate customer tags,including customer’s features& preference, range of activities. This will help us to:• Know customer better• Do customer care• Recommend appropriate

product to customers• Remind customers about

the usage of resources in time

② WLAN logs

Use Case2: Assist Marketing Decisions

— precision marketing

Send e-coupons of the shopping mall to

customers

Send e-coupons of Starbucks Coffee Bar

to customers

Based on customer’s info, including:�tags�sex�age�ARPU�range of activities�usage of Internet�usage of voice call,SMS, etc�social attribute�browsing history on related e-commerce website�Shopping history on related e-commerce website

�Target users of Starbucks Coffee Bar

�Target users of the shopping mall

�Near shopping mall on weekends

�At Central Business District on workdays� There is Starbucks Coffee Shop

nearby(for example, within 200 meters)�At 11:30

1、Choose target usersfor e-coupons

2、Define rules about when to send e-coupons

Big Data

Analytics

System

Precision Marketing Platform

1Analytics and pick up the target users

3Personal Recommend-action Engine① Algorithm② Rules

Choose time slot① Dinner time on

weekdays② Night time near

shopping malls

Marketing Scene Settings① Send electronic

e-coupons

2

Signaling,User location info

User-defined settings:1)receive or not2)parameters

Match and decide the

target users(near real-time)

3、example

Send e-coupons of Starbucks Coffee

Shop to this person

� With the development of digital service, digital traffic puts strain on 2G network.

� Based on the following model, we can analyze the network,,,,service,,,,customer and terminal

info under 2G/3G/WLAN and support the synergic utilization and expansion of these networks.

Use Case3:Optimize Network Performance— synergic utilization and expansion of 2G/3G/WLAN networks

2G cells with high load2G cells with high load endendLow/normal

3G coverage analysis3G coverage analysis WLAN coverage analysisWLAN coverage analysis

Service analysis

Service component

analysis

Service component

analysis

Traffic analysis of

associated TD cells

Traffic analysis of

associated TD cells

Traffic analysis of

associated WLAN hotspot

Traffic analysis of

associated WLAN hotspot

No

High

Performance analysis

Network coverage analysis

YesYesNo

Fit for TD Fit for WLAN

TD quality analysisHigh

Low

Abnormal

normal

TD terminal analysis

few many

AP quality analysisHigh

Low

Abnormal

normal

WIFI terminal analysis

few many