Huawei Technologies at Smart Data Innovation Lab, KIT
October 2016
Dr. Walter Weigel
VP of European Research Institute
Huawei is a leading ICT company
Carrier : 77% of Huawei's revenue
generated from the carrier network
business; from world'...
Telecom, a fast changing industry, what will be the future?
1980s
Voice
1990s
Voice/SMS
2000s
Data/HTML
2010s
Video
2020s
...
IT, a fast changing industry, what will be the future?
1980s
Mainframes
1990s
Process
Computers
2000s
PCs, Servers
2010s
C...
18 local R&D-sites in 8 countries with 1600 jobs
Ipswich
Dublin & Cork
Munich
Milan
Leuven
Paris
Nice
Gent
Nuremburg
Berli...
1600 researchers in Europe at 18 sites
Close to customers, close to industrial partners, close to academic partners
Goal: ...
Cooperation landscape in Europe (2015)
3+
5+
0.2+
31+
4+
10+
20+
5+
5+
2+
2+
0.8+
3+
0.7+
Unit: Million in Euros
Note: All...
Huawei joining SDIL
 We are delighted to join the distinguished SDIL members
 Intend to be a proactive member of the com...
FusionInsight Big Data Platform
Huawei Technologies
Big Data as a foundation for Innovation
HUAWEI Big Data PlatformDB / DW
Credit:
3~5 Weeks
Off Line
Historic Breakdown
Stru...
FusionInsight Big Data Platform
BI Analysis
network signaling
analysis
CRM historical
data Inquiry
Data Collection
Real ti...
FusionInsight Big Data Platform
TelecomBank
FusionInsight
Enterprise
OceanStor
9000
FusionSphereFusionCubeX86 Server
Data ...
Telco Transformation with Big Data
Huawei Technologies
Overview of Selected Telco Big Data Projects
Page 14
Business Services Objectives Huawei Key Offerings Clients
Churn manag...
Churn Management and related Retention Activities
Page 16HUAWEI TECHNOLOGIES CO., LTD.
Churn Management: Predictive Models for Churn Prevention
Can predict
likely churns
K...
Promotion Sensitive
Tariff Sensitive
Product
Sensitive
Communication fee
promotion
On-net Age Promotion
Entertainment
News...
Training Data
Prediction
Indexes
Demographics
Account
Information
Behavior
Information
ContactsCycle
Targeted Customer
Cla...
Churn reason Churn reason details
Category
Solution
Category Subcategory
Disappointment
churn
Operators seldom launch prom...
Copyright©2016 Huawei Technologies Co., Ltd. All Rights Reserved.
The information in this document may contain predictive ...
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SDIC'16 - FusionInsight als Big-Data-Plattform - Eine Fallstudie aus der Telekombranche

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FusionInsight als Big-Data-Plattform - Eine Fallstudie aus der Telekombranche;
Dr. Walter Weigel, VP Huawei European Research Institute;
1st Smart Data Innovation Conference (SDIC'16)

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SDIC'16 - FusionInsight als Big-Data-Plattform - Eine Fallstudie aus der Telekombranche

  1. 1. Huawei Technologies at Smart Data Innovation Lab, KIT October 2016 Dr. Walter Weigel VP of European Research Institute
  2. 2. Huawei is a leading ICT company Carrier : 77% of Huawei's revenue generated from the carrier network business; from world's top 50 carriers Enterprise: Serving more than 100 global top 500 companies Consumer : raising the brand awareness to 65%  Leading global ICT solutions provider  A Fortune Global 500 company, ranking 285 in 2014  Interbrand Top 100 Best Global Brands  170,000+ employees worldwide  45% or 76,000+ employees engaged in R&D  LinkedIn World's 100 Most InDemand Employers Who is Huawei  US$ 60B revenue in 2015  Serving 1/3 of the world's population Market Progress Employees Business Areas
  3. 3. Telecom, a fast changing industry, what will be the future? 1980s Voice 1990s Voice/SMS 2000s Data/HTML 2010s Video 2020s HD/VR/AR 2G 3G 4G 5G 1G GSM WCDMA HSPA LTE LTE- Advanced GPRS 2Mbps 10Mbps 100Mbps 1Gbps 10Gbps 100Kbps 10Kbps ??
  4. 4. IT, a fast changing industry, what will be the future? 1980s Mainframes 1990s Process Computers 2000s PCs, Servers 2010s Cloud platforms 2020s HPCs IBM Evolution HPC & Flash Memory Siemens Bull DEC Apple Nixdorf HP Compaq GigaFLOP (1x109) 1984 TeraFLOP (1x1012 ) 1999 PetaFLOP (1x1015 ) 2008 ExaFLOP (1x1018 ) 2019 ZetaFLOP? (1x1021 ) Beyond 2020 2.5 Tb/cm2 202050 Gb/cm2 20101 Gb/cm2 2000
  5. 5. 18 local R&D-sites in 8 countries with 1600 jobs Ipswich Dublin & Cork Munich Milan Leuven Paris Nice Gent Nuremburg Berlin Gothenburg Lund Helsinki Stockholm Bristol Cambridge Huawei European Research Institute: Structure Darmstadt Establishment in Stockholm2000 Dec 2007 Apr 2009 Mar 2009 Dec 2008 Total People in Sweden 50+ Establishment of Bonn CentreMar 2008 Jun 2008 Establishment of Milan Branch Major Movement from Bonn to Munich Establishment of Gothenburg branch Establishment of Belgium Branch Jan 2012 Establishment of UK Branch Sept 2011 Establishment of Nuremberg Branch Dec 2012 Establishment of Finland and Ireland branches Mar 2016 Acquisition of CaliopaAug.2013 Establishment of France BranchOct.,2013 Aestethics research FranceMarch 2015 Quantum Commun. Germany
  6. 6. 1600 researchers in Europe at 18 sites Close to customers, close to industrial partners, close to academic partners Goal: accelerate ICT innovations of future life and future work for a global market Huawei European Research Institute: Overview Telecom IT ITS / Mobility E-/M-Health Industries 4.0 Smart Grid Smart City Wireless Networks Key Technical InnovationsIndustrial Solutions Fundamental R&D Cloud and Big Data Optical System Terminals and IoT + + New Theories New Algorithms New Materials New Components New Devices
  7. 7. Cooperation landscape in Europe (2015) 3+ 5+ 0.2+ 31+ 4+ 10+ 20+ 5+ 5+ 2+ 2+ 0.8+ 3+ 0.7+ Unit: Million in Euros Note: All projects are Huawei Funded.
  8. 8. Huawei joining SDIL  We are delighted to join the distinguished SDIL members  Intend to be a proactive member of the community, supporting research  Making hardware and the FusionInsight Big Data platform available for projects  Looking forward to working with the SDIL team, board members and with project teams from corporations and universities, across all industries and areas of research  Thank you for giving us this opportunity! -------------------------------------------------------------------------------------------------------------------  A brief look at the FusionInsight Platform  An example of a recent Huawei project with Big Data
  9. 9. FusionInsight Big Data Platform Huawei Technologies
  10. 10. Big Data as a foundation for Innovation HUAWEI Big Data PlatformDB / DW Credit: 3~5 Weeks Off Line Historic Breakdown Structured Data Structured, Semi-Structured, Unstructured Data Credit 2~5 Seconds On Line Historic Breakdown Possible Assets Financial Networking Targeted Marketing Service Innovation Traditional service …
  11. 11. FusionInsight Big Data Platform BI Analysis network signaling analysis CRM historical data Inquiry Data Collection Real time data BOSS StructuredData CRM Other System …… Web log Unstructureddata DPI …… Internet Data Backward Web crawler IDE & OM precision marketing Multi-tenant Parallel Data Mining (Customer Profile) Streaming Big Data Platform (FusionInsight) Map Reduce …… …… X86 Server Cluster detailed statement inquiry third party Data Service Data App Short storage period, bad Customer satisfaction High cost by RISC Server and SAN …… …… Difficulty with Scale-out Performance bottleneck in inquiry Challenges Customer Service ……
  12. 12. FusionInsight Big Data Platform TelecomBank FusionInsight Enterprise OceanStor 9000 FusionSphereFusionCubeX86 Server Data insight: Parallel algorithms、Modeling、… Off-line/Near-line data In-memory iteration Real-time Processing Manager API API API APIPacking Services Big data infrastructure  Simple • Life-cycle data management • User-defined dashboard • Redevelopment widgets  Reliable • HA components & DR • Distributed architecture • N+M data protection  Real-time • Real-time processing • Industry-leading storage performance  Smart • Deep insight based on full data • Automated storage tiering Supports 1000+km Disaster Recovery & Classified Protection of Financial Industry
  13. 13. Telco Transformation with Big Data Huawei Technologies
  14. 14. Overview of Selected Telco Big Data Projects Page 14 Business Services Objectives Huawei Key Offerings Clients Churn management Reduce churn Predict churn accurately, categorize churn reason and propose solutions CMCC, China Unicom, Telkomsel, Traffic management Increase traffic scale and value Drive traffic monetization thru personalization and user lifecycle value development CMCC, China Unicom, Mobily, Du, Vodafone, PLDT, S.A. Telkom, … Internet Operation Smart operation to optimize, personalize and monetize content, services and user experience Big data enabled precise marketing/sales solution to optimize, personalize and monetize data services China Unicom Intelligent location Monetize data assets B2B/B2B2C business collaboration and trading platform CMCC, Facebook
  15. 15. Churn Management and related Retention Activities
  16. 16. Page 16HUAWEI TECHNOLOGIES CO., LTD. Churn Management: Predictive Models for Churn Prevention Can predict likely churns Know your customers. Develop algorithms to predict behavior. Staying a step ahead of the/each customer is an important step in preventing churn. Potential Churn CUSTOMER VALUE MODEL Input Data Algorithm Customer Value (Grade) CHURN PREDICTION MODEL PRE-ALARM INDEX LIBRABY Prediction Algorithm Pre- alarm Model CHURN MODEL
  17. 17. Promotion Sensitive Tariff Sensitive Product Sensitive Communication fee promotion On-net Age Promotion Entertainment News Business Life associated Service Tools Service Toll Discount Preference Family and Friend VPN Preference Package Discount 1 VIP Service Club Score Characters Segmentation Customer Needs Amazing Service Service Sensitive Service Product Price Promotion 2 3 4 6 8 7 9 10 11 12 13 14 16 15 Terminal Promotion Communication5 Insensitive Customer Do not want to any promotion and service. They used to consume regular tariff and service. 17Sloth Churn: Customer Insight & Classification is essential
  18. 18. Training Data Prediction Indexes Demographics Account Information Behavior Information ContactsCycle Targeted Customer Classification Prediction Algorithm Pre-alarm Model Build a core customer pre-alarm index library. Using time window analysis method and classification algorithm like Logistic regression to generate prediction model Outcome •Time •MSISDN •Churn Probability Score •Pre-alarm Level •Churn reason Execution Prediction Output the Result Customer Insight with Predictive Algorithms
  19. 19. Churn reason Churn reason details Category Solution Category Subcategory Disappointment churn Operators seldom launch promotions. Promotion-sensitive Airtime promotion Top up promotion Big promotions for new subscribers rather than old subscribers Promotion-sensitive Promotion for staying with operators Promotion based on tenure Cell phone losing and high fare for new SIM application Tariff-sensitive XXX Decrease fare for new SIM application No personalized tariff plan or promotions for individual users Tariff-sensitive Low tariff preference Personalized tariff plans Service-sensitive Surprised service preference Service remaining and customer care Competition churn Low tariff from competitors Tariff-sensitive Low tariff preference Lease fare reduction off-peak tariff reduction Natural churn Work location change Promotion-sensitive Airtime promotion Roaming promotions Subscriber migrate to other place Promotion-sensitive Promotion for staying with operators Keep phone number for a specific period. Malice churn Malice arrearage Tariff-sensitive Tariff plan promotion preference High call fare remaining and arrearage alarm; Promotion based on tenure Agency channels encourage users to churn and get commission Promotion-sensitive Airtime promotion Delay commission payment to Agency channels. Differentiating Reasons and identifying Solutions
  20. 20. Copyright©2016 Huawei Technologies Co., Ltd. All Rights Reserved. The information in this document may contain predictive statements including, without limitation, statements regarding the future financial and operating results, future product portfolio, new technology, etc. There are a number of factors that could cause actual results and developments to differ materially from those expressed or implied in the predictive statements. Therefore, such information is provided for reference purpose only and constitutes neither an offer nor an acceptance. Huawei may change the information at any time without notice. www.huawei.com Thank you

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