- Gain insight into how requirements on higher data performance increases at an exponential rate - Find out why a tight relationship with customers is key and how to adopt diverse data and real-time analysis tools - Learn why a brand new efficient infrastructure platform is needed for big data and how to build it

1. www.huawei.com
The Efficient Big Data Platform
Petri Pekkarinen, Marketing Director, IT Product Line, Huawei Enterprise
IDC's 360 Degress Conference in Copenhagen January 23rd 2014
HUAWEI TECHNOLOGIES CO., LTD.

2. Contents
1
Huawei Enterprise Introduction
2
The Efficient Big Data Platform
HUAWEI TECHNOLOGIES CO., LTD.
Huawei proprietary. No spread without permission.
Page 2

3. Huawei - A Global Company
A Global Footprint
Germany

14 regions and 140+
branches with business
operations

150,000 employees from
150+ countries

28 joint innovation centers
and 45 training centers
The
Netherlands
Hungary
Romania
Bahrain
India
UAE
China
Mexico
Shenzhen-based HQ
Accounting Shared Services Center
Bid center (in construction)
Logistics center and transit station
R&D center
Training center
Technical assistance center
Malaysia
Brazil
Mauritius
Argentina
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4. Driving ICT Convergence to New Dimension
IT
Consumerization
Client/Processing
terminal/Data terminal
IT
Mainframe
computer/TC
Server/Client
Networking
Collaboration
Security
1950’s
1970’s
1990’s
2000’s
2009
Virtualization
Big Data
Analog
communications
CT
ICT
convergence
era
2013……
Digital
communications
Mobile narrowband
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Mobile
broadband
IT
Mobilization
IT
Virtualization
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5. Huawei Enterprise ICT Product and Solution Portfolio
Bring Your
Own Device
ICT
Software Defined
Network
Cloud Data
Center
Unified Management
UC&C
Telepresence
UC
VC/TP
IVS
Contact Center
Security
Enterprise Network &
Enterprise Wireless
DC Network
Data Center
Infrastructure
IP Network
Server
Storage
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GSM-R/LTE
VDI
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OTN/MSTP/Microwave
Networking Power
Page 5

6. Contents
1
Huawei Enterprise Introduction
2
The Efficient Big Data Platform
Analysis of X in 1 Big Data Technology
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7. The Digital Universe
2020 = 35 ZB
2013 = 3.6 ZB
2009 = 0.8 ZB
*Zettabyte = 1 trillion gigabytes
*Source: IDC Digital Universe Study
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8. Conflicting 4 V Model
• Large
capacity
• Volumes are
groving
quickly
• Variety of
sources
• Diverse
data types
Volume
Variety
Value
Velocity
• Low value
density
• Near
real-time
responses
IDC: four characteristics of big data
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9. Capacity vs. Performance
Capacity
Performance
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10. Tools to tackle Big Data?
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11. Driving Force of Big Data
1
•
Collection
Storage — open architecture, gradual scale out, and
integration of near-line systems and offline systems
2
Storage
•
Big Data
Analysis — compound data, unified storage of multiple data
sources, unified query, and sharing of storage resources
3
•
Management
Archiving — lifecycle management of mass data at a low cost
and high energy efficiency
4
Analysis
•
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Maintenance — easy to use
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12. Paradigm shift in Big Data architecture design
Core
Paradigm shift in big data
architecture design
Proprietary
Hardware
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Commodity
Hardware
Central
Storage
Distributed
Storage
Scale-up
Scale-out
Serial
Computing
Parallel
Computing
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Big Data
Life Cycle
Platform

13. Core
Best efficiency platform
of big data
Huawei Big Data Storage Strategies
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Maximized data value
Fine-grained data lifecycle
management on a single platform
Fundamental innovation philosophy
3 in 1 architecture
Advanced platform architecture
Industry's highest-performance
distributed big data storage system
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14. Big Data Life Cycle Platform
Flexible Scale-Out
Platform
Efficient and
Intelligent
Unified Management
Reliable and
redundant
Big Data
Life Cycle
Platform
Information silos
eliminated
Multiple interfaces
and ability to
integrate
Big Data Infrastructure must achieve high efficiency besides meeting the
requirements of capacity, performance and diversity of data
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15. Big Data in Practice
Mount Sinai
Spotify
Amazon
Bank data
repository
• Mount Sinai hospital in
New York optimized its
patients first 8-12 hours
in hospital by running
hundreds of simulations.
• Achieved financial effect
of adding 100 new beds
without actually adding
new
• The heart of Spotify is a
massive and growing
data-set.
• Most data is usercentric
• Data is utilized to
provide music
recommendations,
advertisement and
many other things.
• Amazon harvests the
buying patterns
(transactions) or its
customers to
recommend
complementary
products for up-sell.
• It also uses communitygenerated ratings and
tips to further guide
buying decisions
• Customer data
predicted to grow
from 2 PB to 9 PB by
2015.
• Big Data solution
applied to
compliance
requirement of
keeping customer
transaction records
for 15 years.
Source: Supply Demand Chain Executive 2013, Spotify Labs 2013
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16. Getting Started with The Big Data Initiative
MEASURE
Measure
RESULTS
results
Define
Objective
Activate
teams
Implement
Activity
Be Strategic.
Get tactical.
Be analytical.
Get Buy-in.
Figure out the
business case. What
are your business
goals?
Decide what
questions need to be
asked. What are the
pain points?
Where the data will
come from?
Identifying right data
is the key.
Get buy-in from the
whole team and
locate right people.
Big Data is all about
team work.
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17. Thank you
www.huawei.com
Copyright©2011 Huawei Technologies Co., Ltd. All Rights Reserved.
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