Big Data: Industry trends and key players

SYNC.
Global investment themes: Telecoms, media and technology

Big Data

2 May 2012

Cyrus Mewawalla www.researchcm.com CM Research
Authorised and regulated by the Financial Services Authority

TMT Investment Themes Big Data 2 May 2012

Contents

WHAT IS BIG DATA? .................................................................................................................................... 3

GLOBAL MARKET FOR BIG DATA ............................................................................................................ 4

BIG DATA TRENDS ....................................................................................................................................... 6

WIDER TRENDS IN THE COMPUTING SECTOR ................................................................................... 7

INTERNET COMPANIES ............................................................................................................................. 13

DATA STORAGE, NETWORKING AND HARDWARE COMPANIES ................................................ 15

ENTERPRISE SOFTWARE COMPANIES ................................................................................................ 18

CYBER SECURITY COMPANIES ............................................................................................................... 21

TELECOM OPERATORS ............................................................................................................................. 22

OTHER INVESTMENT THEMES ............................................................................................................... 23

OUR RESEARCH APPROACH .................................................................................................................... 24

IMPORTANT DISCLOSURES ..................................................................................................................... 25

ABOUT CM RESEARCH............................................................................................................................... 25

www.researchcm.com 2


What is big data?
 Big data is data that cannot be analysed on a traditional database
 Companies that develop the database platforms to analyse big data will make a fortune

The digital unit scale Big data is the next technology problem looking for a solution
Unit Symbol Size Today, there is a deluge of data on the internet. It comes from web crawlers (spiders), web robots (bots), web logs
Bit b 0 or 1 (blogs), emails, videos, tweet streams, genome sequences, traffic-flow sensor data, banking transactions, GPS
Byte B 8 bits
Kilobyte KB 1,000 B trails and much more. This data, if properly interpreted can be used defensively to combat theft, fraud, cyber-
Megabyte MB
6
10 B attacks or terrorism; it can also be used commercially to target sales or provide business intelligence. So it is
9
Gigabyte GB 10 B valuable to governments, banks, marketing agencies, social networks, retailers and business information providers.
12
Terabyte TB 10 B
15
But there is a problem: it is so complex that it cannot be processed using conventional methods. The big money
Petabyte PB 10 B
18
lies in developing the analytical engine that can intelligently interpret big data.
Exabyte EB 10 B
Zettabyte ZB
21
10 B
Big data’s characteristics make it difficult
24
Defining big data to analyse
Yottabyte YB 10 B
Big data refers to any data that cannot be analysed by a traditional V3= High Volume, High Velocity and High Variety
Source: CM Research
database due to three typical characteristics: high volume, high
velocity and high variety:

 High volume: big data’s sheer volume slows down traditional database racks
 High velocity: big data often streams in at high speed and can be time-sensitive
 High variety: big data tends to be a mix of several data types, typically with an
element of unstructured data (e.g. video), which is difficult to analyse

Much of this data, if properly analysed, can provide companies a competitive advantage. But
traditional relational databases – such as Oracle, Microsoft’s SQL Server or IBM’s DB2 – are
not capable of handling this kind of data. So new technology platforms are required.
Source: IBM



Global market for big data
 Digital information is growing at 57% per annum globally
 With global social network penetration and mobile internet penetration both under 20% this growth has only just begun
 All the data generated is valuable, but only if it can be interpreted in a timely and cost-effective manner
 IDC expects revenues for big data technology infrastructure to grow by 40% per annum for the next three years

Industry size
In 2006, IDC estimates that the world produced 0.18 zettabytes of digital information. It grew to 1.8 zettabytes in 2011 and will reach 35
zettabytes by 2020. That translates to a ten-fold increase over the last five years and an astounding 29-fold increase over the next ten
years. This year, the world’s digital information is expected to grow by 57%. Within that, internet traffic is growing by 35%, and mobile data
traffic at 110%, according to Cisco. The big data industry is worth somewhere between $30bn and $200bn.

Globally, all kinds of data are growing fast
Digital information is growing at 57% IP traffic is growing at 35% Mobile data traffic is growing at 110%
Total stored digital information in world Global IP traffic by type Global mobile data traffic by application type
14 80,000 12,000
VoIP
12 70,000
10,000 Video
60,000 Online gaming
10
Video calling 8,000
Zettabytes

PB/month
50,000
PB/month

8 Data
40,000 Web, email 6,000
6
30,000 Internet video File sharing
4,000
4 20,000
File sharing 2,000
2 10,000 Other (M2M,
Business gaming, VOIP)
0 ‐ ‐
2006 2008 2010 2012 2014 2010 2011 2012 2013 2014 2015 2011 2012 2013 2014 2015 2016
Source: IDC, Cisco, CM Research

Growth drivers
Smartphones, tablets, sensors, social networks, online games, video streams and mobile payments will all drive big data for many years to
come.



Investment risks
Whilst big data industry revenues are certain to grow, investors face significant risks.
Bandwidth risk
Today, internet bandwidth prices are capped, effectively making internet bandwidth a free resource for big data companies. But, without
substantial investment by the world’s mobile operators, big data is likely to grow far faster than the ability of the network to carry it. As
networks get overloaded, network latency rises, reducing the speed and efficiency of analytical engines, especially those powered through
the cloud. The coming mobile bandwidth shortage will shift competitive advantage from technology companies to telecom operators.
Open source risk
As we explain in the “Supply Chain” section on pages 6 to 11, the most commonly used big data technology platform today is Hadoop,
based on open source software. Even the world’s leading big data players – from IBM to Oracle – use Hadoop as the basic framework for
their big data appliances, though they add value by writing the applications that run on it. Nonetheless, with the source code free, barriers
to entry remain low. In the longer term, this may depress the database industry’s margins.
Patent risk
Ever since Apple took on the mobile phone industry – and won – with barely a handful of mobile patents to its name, a patent war has
erupted across the technology sector. Were a patent war to break out in the big data space, technological progress could be slowed down.
Whilst regulators are unlikely to allow any hoarding of patents on anti-competitive grounds, the risk remains. Oracle, a leader in big data, is
well known for filing multi-billion dollar patent infringement lawsuits against its competitors.
Cyber risk
Last month Global Payments, a credit card transaction processor, admitted that hackers had stolen the details of 1.5m North American
card holders. This is the latest in a string of security breaches that have hit companies dealing in big data. Apple, EMC, Google, Oracle and
Sony are all recent hacking victims. As the level of cyber-crime rises, so does the risk of dealing with big data. Just as the Fukushima
incident dampened prospects for the nuclear sector, so a large cyber-attack could adversely impact big data industry profits.
Regulatory risk
In addition to security risks, regulators are clamping down on data privacy. The US, Europe and several Asian countries are looking at
revising their data compliance and data privacy laws. That could limit the production and consumption of data by both businesses and
governments. Big data can also fall fowl of copyright laws. As the amount of digital data flowing through analytical engines grows, so do the
risks of bigger regulatory breaches – and fines.



Big Data Trends
 Traditional database companies like Oracle and IBM face disruptive threats from open source and cloud platforms
 The real money is likely to be in business intelligence, rather than databases
 Much of the innovation – especially in terms of database business models – is in the cloud

As the big data industry evolves, four trends are emerging.

1. Unstructured data: Data is moving from structured to unstructured format, Unstructured data is expensive to analyse
raising the costs of analysis. This creates a highly lucrative market for Big data classification
analytical search engines that can interpret this unstructured data. Ease of use Classification Data type
2. Open source: Proprietary database standards are giving way to new, open
source big data technology platforms such as Hadoop. This means that Databases
barriers to entry may remain low for some time. Easy and cheap to analyse Structured data XML data
3. Cloud: Many corporations are opting to use cloud services to access big data Data warehouses
Enterprise systems
analytical tools instead of building expensive data warehouses themselves.
This implies that most of the money in big data will be made from selling Social media
hybrid cloud-based services rather than selling big databases. Voice, music & video
Unstructured
4. M2M: In future, a growing proportion of big data will be generated from Difficult or expensive to analyse
data
Documents
Email
machine to machine (M2M) using sensors. M2M data, much of which is
business-critical and time-sensitive, could give telecom operators a way to
profit from the big data boom. RFID
GPS
Requires extensive infrastructure Sensor data QR
(machine‐to‐machine)
Structured vs. unstructured data Temperature
Industry commentators normally classify big data into two categories: structured data Source: CM Research
and unstructured data. Structured data – such as that found in a corporate database
– is relatively easy to analyse. Unstructured data, which includes voice, video, email and documents, can be difficult – and expensive – to
analyse.



Wider trends in the computing sector
 We are witnessing a paradigm shift in computing from the PC generation to the cloud generation
 This changes the way data is stored and accessed
 The computing value chain will now focus around data, rather than hardware or software
 The market leaders in this new data-centric computing world include Amazon, Check Point, Citrix, EMC, Facebook,
Google, Red Hat, Riverbed, Salesforce, Teradata and VMware

Tablets are replacing PCs
This year, about 365m PCs will be shipped, dwarfing expected tablet shipments of 74m. But by 2015, tablet shipments are likely to
overtake PCs, on current growth trajectories. Because of the way that tablets – and smartphones – store and access data, this trend will
boost cloud services.
Apps and social networks also impact the way we use computers
The app revolution, social networks and advances in remote access technologies are also changing the way we use computers. As a result,
it can be quite difficult to set out a framework for investors that adequately captures all these interconnected themes.
… leading to a new computing paradigm
Some analysts group these themes under the heading “Big Data” (or data which cannot be analysed on a traditional database). Others call
it “cloud computing”. What is important is not the terminology, but the fact that these changes in the way we use computers are, collectively,
highly disruptive. We decided to dissect Watch list: The cloud generation will create a new set of winners along the computing value chain
the main parts of the global technology HARDWARE SOFTWARE SERVICES
sector – hardware, software and services – Databases Storage Servers Networking Operating Analytics Security Cloud Virtualisation IT services Data centres
summarising how each will be impacted by equipment systems applications

the next generation of computing IBM EMC Cisco Brocade Apple Amazon Check Point BMC SoftwareCitrix Systems Accenture 21Vianet
Oracle HP Intel F5 Networks Google Facebook Fortinet JDA Software Microsoft Informatica Amazon
technology.
SAP NetApp Lenovo Riverbed Oracle Google Qihoo 360 Neusoft Red Hat Infosys Rackspace
Salesforce Teradata Quanta UTStarcom Red Hat IBM Sourcefire Open Text VMware TCS Telecity
Source: CM Research



Big Data Supply Chain
The main trends in big data management are:

 Databases: these are moving What does the big data supply chain look like?
away from relational databases
(e.g. Oracle or SQL Server) to Big Data Production Big Data Management Big Data Consumption
new database technologies such
as NoSQL Storage
Data Mining
Social media
 Processing: new, distributed Documents
Volume Security
database platforms such as Databases
Web crawlers Search
Hadoop are emerging, that can Velocity
Web robots (bots)
process semi-structured data far Sensors Big Data
more cost-effectively than Voice quality
Music & video
Digital Marketing
traditional database tools Email Variety
RFID Analytics
 Analytics: the value-add has Call records
Re‐selling
Payment details
moved from databases to GPS Databases
analytics – all the big database
companies (IBM, SAP, Oracle)
have been on an M&A spree, Gather raw data on industrial scale Improve big data quality Commercialise big data
buying up business intelligence
software houses such as Netezza Source: CM Research

and Aster Data

 Appliances: many big data players are merging their software and hardware to create “big data appliances” that provide one-stop
solutions for big data analytics

 Cloud services: companies are moving from building expensive databases in-house to accessing someone else’s database
infrastructure from the cloud



A brief history of databases
Today, 90% of data warehouses hold less than 5 terabytes of data. Yet Twitter alone produces over 7 terabytes of data every day! As a
result of this data deluge, the database industry is going through a significant transformation. Here is a quick update on the story so far of
the global database industry.
Historically, relational databases were the industry standard…
Oracle is the market leader in databases
The most popular database technology used today for capturing business data is the
relational database management system (RDBMS), which was first created in the Database market share by revenues, 2011
1970’s.These relational databases are made by the likes of Oracle, IBM and Microsoft Others
12%
and use a computer language called SQL (Structured Query Language) to define, query
SAP
and update the database. 3%

… but these databases were not capable of handling big data… Oracle
42%
Over the last decade, business data has changed dramatically, creating two problems Microsoft
for traditional database makers: first the sheer size of the data has increased into the 19%
petabytes range; and second the majority of business data that needs to be analysed
today comes in unstructured format, such as email or video. To deal with the first
IBM
problem, RDBMS platforms typically scaled up vertically, by adding more CPUs or more 24%
memory to the database management system. The second problem could not be dealt Source: Company data, IDC, Gartner, CM Research

with at all because relational databases simply cannot categorise unstructured data.
…so new databases like NoSQL and new processing platforms like Hadoop emerged…
The first businesses that had to deal with big data were the leading internet companies such as Google, Yahoo and Amazon. Google and
Yahoo, for example, ran search engines which had to gather unstructured data – like web pages – and process them within milliseconds to
produce search rankings. Worse, they had to deal with millions of concurrent users all submitting different search queries at once. So
Google and Yahoo engineers designed entirely new database platforms to deal with this type of unstructured query at lightning speed.
They built everything themselves, from the physical infrastructure to the storage and processing layers. Their technique was to scale out
horizontally (rather than vertically), adding more nodes to the database network. Horizontal scale out involves breaking down large
databases and distributing them across multiple servers. These innovations resulted in the first “distributed databases” and provided the
foundation for two of today’s most advanced database technology standards, commonly referred to as NoSQL and Hadoop:



New database technologies

 NoSQL: a broad class of database which does not use SQL as its primary query language and is designed to handle semi-
structured data (though without the level of data integrity associated with RDBMS)

 Hadoop: a distributed database processing platform designed to store and analyse big data across several thousand nodes

Together, NoSQL and Hadoop provide a framework for analysing big data in a fast and cost effective manner. Both are open source and
both lower costs by storing data in smaller chunks across several servers. They are able to process queries fast by sending several
queries to multiple machines at the same time. Their main advantages are their low cost, high speed and high degree of fault tolerance.
Their main disadvantage is they are not as accurate or complete as relational databases.
Both Hadoop and NoSQL are now being embraced by the database incumbents
In recent years, IBM and Oracle have acknowledged that their core RDBMS platforms are not designed to cope with big data. Together
with Microsoft, EMC, Teradata and other big data industry leaders, they have incorporated emerging database technologies like NoSQL
and Hadoop into their own big data platforms. Hadoop and NoSQL are now used by Oracle
There is a risk that open source database platforms may lower industry
margins
Whilst most relational databases were proprietary, Hadoop is open source. Some
say that lowers barriers to entry and threatens the profit margins of the leading
database players. The most exposed are Oracle and IBM, who own 42% and 24% of
the database market respectively. But this risk may be overblown. Red Hat is a
$12bn enterprise software company that specialises in open source solutions.
Moreover, while Hadoop provides the basic infrastructure to cope with big data,
software developers still need to write the business intelligence code that sits on top
of it, so there is significant scope for each of the big players to differentiate
themselves, despite basing their big data appliances on an open source product.
Source: Oracle



ANALYTICS
The lesson that Amazon, Google and Business intelligence tools feature high in the target list for large technology companies
Facebook all learnt early on in the digital The chart shows the transaction value (in $bn) of recent M&A deals in the big data technology space
age was that in order to build really fast big SAP  acquires Success Factors (Online HR software)
data engines you need all the ingredients to Oracle acquires RightNow (Cloud computing)
fit perfectly together – the servers, the IBM acquires Algorithmics (Risk management software for…
databases, the networks, the analytical Teradata acquires Aster Data (Data analysis software)
2011 Acer acquires iGware (Cloud computing)
engines and the security. That’s why Dell acquires Force 10 Networks (Data centre networking)
Google decided back in 2002 to build its big Salesforce.com acquires Radian6 (Data analysis software)
data analytical engines itself. Sometime Ericson acquires Telcordia (Enterprise software)
afterwards, the leading players in big data – CenturyLink acquires Savvis (Cloud computing)
Apax acquires Epicor Software (Enterprise software)
like IBM, Oracle, HP, EMC, Teradata – also Apax acquires Activant (ERP software)
came to this realisation. As the M&A chart GGC Software acquires Lawson software (ERP software)
on the following page demonstrates, each Verizon acquires Terremark (Cloud computing)
one of these industry leaders has been Oracle acquires Art Technology (CRM software)
Attachmate acquires Novell (Intelligent workload…
buying up the missing pieces in their EMC acquires Isilon (Data storage software)
portfolio of big data engine components. 2010 Misys acquires Sophis (Application software)
Over the last five years, Oracle, EMC, HP, IBM acquires Netezza (Data analysis software)
HP acquires 3Par (Data storage)
IBM, Microsoft, SAP and Teradata have
Hexagon acquires Intergraph (Mapping software)
collectively spent more than $45bn on IBM acquires Sterling Commerce (B2B software)
buying software, security or storage Warburg Pincus acquires IDC (Information management)
companies. The bulk of this money has SAP  acquires Sybase (Data analysis software)

gone on business intelligence tools such as 2009 IBM acquires SPSS (Data analysis software)
EMC acquires Data Domain (Data storage)
Netezza, AsterData, Hyperion, Business Microsoft acquires Datallegro (Data analysis software)
Objects, SPSS and Cognos. Big data SAP  acquires Business Objects (Data analysis software)
analytics is the new battleground in the Brocade Communications acquires Foundry Networks…
Oracle acquires BEA Systems (Enterprise applications…
technology sector. As databases become
2008 Microsoft acquires FAST Search and Transfer (Enterprise…
open sourced or commoditised, analytical Oracle acquires Hyperion (Data analysis software)
engines will suck out most of the industry’s IBM acquires Cognos (Data analysis software)
profits. 0 1 2 3 4 5 6 7 8
Source: CM Research



How does it all fit together?
The diagramme opposite
Where do the big players fit into the big data supply chain?
summarises how different
technology industries feature in
the big data value chain. Big Data Big Data Big Data
Production Management Consumption
What is interesting is that the big
internet champions like Facebook Operating system and browser software developers
and Google straddle the entire
value chain: they collect data via Social media Search engines
their social network platforms, Documents
Databases Social networks
browsers and operating systems;
Web crawlers
they process it using their custom
Web robots Cloud services providers
database systems; and they use it Sensors
to target advertising dollars to Voice Telecom operators Marketing
customers likely to respond Music & video agencies
positively. Email Data centres
RFID Third party
Analytical engines
They control the data and how it is Call records resellers
used. So while many technology Payment details Hardware makers
GPS
analysts point to IBM and Oracle Data
as the big data champions, Cybersecurity scientists
investors should keep an eye out
Apps developers
for Amazon, Google, Facebook.
Their analytical engines are Source: CM Research
hidden, but highly disruptive.



Internet companies
 The big Internet companies control where the data comes from and where it goes to
 Amazon, Baidu, Facebook and Google may one day make a lucrative side business from selling their proprietary
distributed database technologies, competing with IBM and Oracle

Search engines and internet portals are analytical engines focused on producing business intelligence. That is why they feel so
comfortable in the market for big data. Social networks accumulate valuable data about users’ likes and dislikes. Their in-house databases
and business intelligence tools analyse some of the most complex data in the world. These internet companies have substantial power
because they control the entire big data value chain: they control access to the data; they control the analytical engines that interpret the
data; and they control how it is used. Google’s AdMob marketing platform is an example of this power.

Where do the Internet players sit in the Big Data value chain?
Data Data management Data
production consumption
Databases Analytics, Storage, Security Consulting
applications servers,
Company Sector Country Mkt Cap P/E networking Description
0 US$m 0
0 0 0
Amazon Internet content USA 104,571 91.6 1 1 1 1 Amazon.com is an online retailer offering books, music, video and cloud services
Baidu Internet content China 46,947 28.8 1 1 1 1 1 Baidu operates an Internet search engine.
Facebook Internet content USA 100,000 0.0 1 1 1 1 1 Facebook operates the world's largest social networking website.
Google Internet content USA 198,184 14.0 1 1 1 1 1 1 Google operates a web based search engine.
Microsoft Software (applications USA 271,180 11.9 1 1 1 1 1 1 1 Microsoft develops operating system software, server application software, and cloud servic
Tencent Internet content China 57,921 28.2 1 1 1 Tencent Holdings provides Internet, mobile, internet advertising and social networking servic

Source: Company data, S&P, FT, CM Research *Note: Facebook’s market valuation is based on secondary market estimates



Amazon
Amazon Web Services (AWS) is a global leader in cloud-based infrastructure. It has a host of big data products, including cloud databases
(e.g. DynamoDB), data storage services (e.g. Simple Storage Services, S3) and analytical tools (Elastic Compute Cloud, EC2).
Apple
Apple is not a significant player in big data. The company does not sell enterprise software, database or business intelligence tools, but its
success with consumer products may rapidly catapult it into the business market. Despite its name, iCloud is less of a cloud computing
product than a streaming service.
Facebook
Facebook’s 850m users provide it a lot of big data. In devising ways to analyse this data, the company has changed the economics of the
data centre ecosystem, dramatically lowering costs. It has also launched a number of global initiatives such as Open Compute which
releases some of its in-house database technologies to the world. If it turned its mind to it, Facebook has the skills to develop a world
beating big data analytical engine.
Google
Google was one of the original inventors of Hadoop, the industry standard distributed database platform for big data. It developed the
technology in-house and released the basic framework as open source. Its search engine analytics remain far ahead of the field and its
Android software provides it with a second stream of big data, Google is investing in a suite of big data projects that may yield dividends.
Its storage service, Google Drive, will soon compete with iCloud.
Microsoft
Microsoft is reportedly spending 90% of its $9.6bn annual R&D budget on cloud computing. Azure, its cloud platform has been gaining
traction and SQL Server, is the third largest player in the database market after Oracle and IBM. But Microsoft is hedging its bets by
integrating Hadoop with Azure as well.



Data storage, networking and hardware companies
 Many hardware makers like Cisco, Dell, Lenovo and HP are investing heavily in big data appliances
 Data storage companies are likely to continue to beat earnings expectations as the data deluge goes into overdrive

Data storage, servers and networking equipment are essential for big data to work, but are typically in the bit of the value chain that very
quickly gets commoditised. Like any commodity, however, its price depends on supply and demand. Data storage companies in particular
are likely to see a short term boom as new storage technologies come into play and data production continues to outpace storage.

Where do the data storage, networking and server companies sit in the Big Data value chain?
0 US$m 0
0 0 0
21 Vianet Web hosting China 719 27.2 1 21Vianet is a Chinese Internet data centre services provider.
ARM Chips (wireless) UK 11,647 37.0 1 1 ARM Holdings develops processors, data engines, peripherals, software, and tools, especia
Aruba Networks Telecom equipment USA 2,277 32.4 1 Aruba Networks provides enterprise mobility solutions that enables secure access to data,
Brocade Comms Telecom equipment USA 2,558 9.6 1 Brocade Communications provides switching solutions for storage area networks (SAN).
Cisco Telecom equipment USA 108,392 10.9 1 1 1 Cisco Systems designs, manufactures, and sells IP-based networking products
EMC CE (storage) USA 60,199 16.5 1 1 1 EMC provides enterprise storage systems, software, networks, and services. The Company
Fusion-io CE (storage) USA 2,263 83.2 1 Fusion-io provides data-centric computing solutions through a storage memory platform for
Intel Chips USA 145,126 11.4 1 1 Intel is the world's largest semiconductor manufacturer.
Juniper Networks Telecom equipment USA 11,459 25.9 1 Juniper Networks provides Internet infrastructure solutions for Internet service providers and
NetApp CE (storage) USA 14,730 17.1 1 1 1 NetApp provides storage and data management solutions.
QLogic CE (storage) USA 1,729 12.5 QLogic supplies high performance storage networking solutions
Rackspace Hosting Web hosting USA 7,877 75.1 1 Rackspace Hosting delivers websites, web-based IT systems
Riverbed Tech Telecom equipment USA 3,149 20.7 1 Riverbed Technology manufactures appliances used to connect computers in wide area net
SGI CE (storage) USA 310 40.3 1 1 Silicon Graphics Int. makes large-scale clustered computing, clustered storage and high pe
Telecity Web hosting UK 2,653 26.8 1 Telecity designs, builds, and manages technical, web, and Internet infrastructure for orate c
Teradata CE (storage) USA 11,901 26.9 1 1 1 Teradata offers integrated data warehousing, big data analytics, and business applications.

Source: Company data, S&P, FT, CM Research



ARM
ARM chips are contained in most mobile devices because they consume less power than Intel’s. As data centres – which are largely based
on Intel’s x86 architecture – start to proliferate, there will be a renewed emphasis on power efficiency. ARM is aiming for this market, but
Intel’s forthcoming 3D chip design may be a match for ARM.
Brocade
Brocade Communications makes networking equipment that is specifically designed for data centres. Its products make data centres run
more efficiently. As the data storage market expands, Brocade should ride the wave.
Cisco
Cisco appears to be shifting slowly away from its commodity hardware business of internet routers and switches towards other unrelated
areas such as the smart grid or the television software market. In the realm of big data, Cisco has a history of working with EMC and
VMware and is likely to share in their growth markets of data centres, cloud computing and virtualisation.
Dell
Dell’s strategy is unashamedly targeted at big data. It is rapidly filling gaps in its big data product portfolio by supplementing its strength in
servers and PCs with a number of recent acquisitions. They include Perot systems, an IT services company and Force10 Networks, a
leader in data centre networking. Dell supports Hadoop.
EMC
EMC is a leader in data storage with well-known brands such as Isilon. Through its 80% shareholding in VMware, a leading virtualisation
software company, it is also a leader in cloud offerings. It also has a strong suite of Big Data analytics products including Greenplum which
provides enterprise data cloud solutions.
HP
Whilst HP’s management appears to be in turmoil, its assets in the big data space are quite strong. It recently purchased Autonomy, a
leader in unstructured search analytics, for $12bn. It also acquired 3Par, a data storage company in 2010 and EDS, an IT services
company, earlier. It has its own in-house security software, Fortify, its own database management software OpenView, its own server
hardware NonStop 9000, server software ProLiant and networking products from 3Com.
Intel
Intel’s x86 architecture provides the core processing power for most data centres. That architecture is now dated and very power hungry.
ARM, the leader in mobile processor chip designs, makes CPUs that are more energy efficient and is aiming squarely at data centres. Intel



has promised that its new 3D chip designs will use less energy and also incorporate better security features, following its 2010 acquisition
of McAfee.
Lenovo
Lenovo now owns IBM’s former PC manufacturing business. Last month the Chinese hardware manufacturer announced it had teamed up
with Actian to move into big data appliances. Lenovo’s ThinkServer hardware will combine with Actian’s Vectorwise analytical database to
create a big data appliance capable of running business intelligence tools such as IBM Cognos, MicroStrategy, Pentaho, SAP
BusinessObjects and Tableau.
NetApp
NetApp provides storage and data management solutions. Its enterprise software solutions include virtualization and cloud products. Last
year it launched its E-series platform for big data analytics.
Rackspace
Rackspace was one of the first large-scale data centres and is now a leading cloud services provider. Together with NASA, it was one of
the founders of OpenStack, the open source software project set up to help organisations run clouds for virtual computing or storage.
Seagate
Seagate Technology makes hard disk drives, many of which are specifically designed for enterprise servers, mainframes and workstations.
The company also provides data storage services for small and medium-sized businesses. Data storage, rather than data analytics, is the
key driver of its profits.
Silicon Graphics International
SGI sells servers and storage that are purpose built for large-scale data centre deployments. It specialises in parallel processing scale outs.
Valued at $285m, it is a pure play on the market for data centre infrastructure.
Telecity
TeleCity Group runs data centres in the UK and Europe. It offers businesses telecoms, internet and IT infrastructure through the cloud.
Teradata
Teradata provides data storage facilities to enterprises through a suite of business intelligence tools to help them analyse big data. The
company’s recent acquisition of Aster Data, an SQL based analytical engine that uses Hadoop technology, has enabled it to become a
more credible player in big data appliances.



Enterprise software companies
 Hadoop is fast becoming the industry standard enterprise database platform
 Oracle faces the biggest threat
 Cloud database services are likely to be the fastest growth sector this year within the enterprise software space

Where do the enterprise software players sit in the Big Data value chain?

0 US$m 0
0 0 0
Accenture IT services USA 46,004 16.9 1 Accenture provides management and technology consulting services and solutions.
Adobe Software (applications USA 16,883 13.9 1 1 1 1 Adobe develops, markets, and supports computer software products and technologies.
BMC Software Software (applications USA 6,889 12.6 1 1 BMC Software provides management solutions for mainframe and distributed information tec
CA Inc Software (applications USA 12,904 11.8 1 1 CA designs, develops, markets, licenses, and supports standardized computer software pro
Citrix Systems Software (applications USA 16,143 31.5 1 1 Citrix Systems designs, develops, and markets virtualisation solutions that allow application
CommVault Software (applications USA 2,355 54.5 1 CommVault Systems provides data management software applications and related services
Informatica IT services USA 5,125 29.4 1 Informatica provides data integration software and services.
Infosys IT services India 26,835 16.9 1 Infosys provides IT consulting and software services, including e-business, program manage
IBM IT services USA 240,848 13.9 1 1 1 1 1 IBM provides a range of computer services
Intuit Software (applications USA 17,320 19.9 1 Intuit develops accounting software solutions for small and medium sized businesses
Oracle Software (applications USA 147,761 12.3 1 1 1 1 1 Oracle supplies software for enterprise information management.
Progress Software Software (applications USA 1,456 18.6 1 Progress Software develops databases, enterprise applications and integration software
Red Hat Software (applications USA 11,778 51.4 1 1 1 Red Hat develops and provides open source software and services, including the Red Hat Li
Salesforce.Com Software (applications USA 21,715 98.4 1 1 Salesforce.com provides CRM software on demand.
SAP Software (applications Germany 81,391 16.6 1 1 1 SAP develops databases and business software, including e-business and enterprise mana
TCS IT services India 46,311 22.9 1 Tata Consultancy Services is a global IT services organization
VMware Software (applications USA 48,145 41.7 1 1 1 VMware provides virtualization solutions from the desktop to the data centre.




Adobe
Adobe is an applications software player with a difference. Through its software-as-a-service (SaaS) products offered via 23,500 servers
and networked devices in 19 data centres, Adobe captures more than 6 trillion transactions per year for its 5,000 digital marketing
customers, amounting to 27 petabytes of data. As a result, it has just added new predictive analytics capabilities to its Adobe Digital
marketing Suite to help marketers sort through big data more effectively.
Citrix Systems
Citrix provides enterprise software products including its XenServer hypervisor (a programme that enables multiple operating systems to
run concurrently), virtual desktop tools and cloud operating systems. Its various cloud-based products will see it ride the wave of big data.
Fujitsu
This year, Fujitsu, the Japanese technology giant, has launched a range of big data products. They include its Data Utilization Platform
Services, which use cloud services as a platform for analysing big data as well as its Interstage Big Data Parallel Processing Server V1.0,
a database software package that uses Hadoop.
IBM
IBM is the undisputed leader in big data. It has a complete array of products all across the value chain from hardware to middleware,
databases, security software, cloud applications and IT services. In addition, over the last five years, it has acquired a string of data
analysis firms – including Cognos, SPSS, Netezza and Algorithmics to name but a few. IBM is one of a handful of companies that can
claim to be within a whisker of artificial intelligence. In early 2011, its supercomputer, Watson, demonstrated in a US television game show
called Jeopardy, that it was able to beat the all-time champion of the general knowledge quiz show by a large margin. The challenge for the
IBM engineers who built Watson was not to just to create an encyclopaedia of “facts” that could answer any query in less than three
seconds, but to create a machine that could “think” like a human. Given the sophisticated nuances of many of the quiz show’s questions,
many would say that IBM succeeded. Watson turbo-charged analytical engine is a huge asset to IBM’s Big Data platform and is being used
to serve the business intelligence needs of many of its corporate clients, including WellPoint, AstraZeneca, Bristol-Myers Squibb, DuPont,
Pfizer and Nuance Communications.
Informatica
Informatica specialises in data integration and data quality software. One of its strengths is its independence. Since it does not make its
own hardware or software, it is able to take a technology neutral stance, choosing the best combination of kit for its customers’ big data
requirements. If truly disruptive technologies hit the database market soon – and that is likely – then Informatica is one of the best placed
larger players to benefit from them, given its lack of allegiance to legacy systems.



Oracle
With a 42% market share, Oracle is the global leader in database solutions. Despite the open source threat, Oracle has embraced Hadoop
and NoSQL in its recently launched Big Data Appliance. Through its 2009 takeover of Sun Microsystems, Oracle already owns Java (the
open source language in which Hadoop is written). Like its rivals, Oracle has been busy in recent years acquiring business intelligence
companies such as Endeca, RightNow, Art Technology and Hyperion. Today, however, with threats to its core database business coming
simultaneously from several fronts – open source databases, rapidly evolving cloud business models and the advance of super data
centres built by the likes of Amazon – its business model is under siege.
Red Hat
Red Hat is living proof that big money can be made from open source software. Its flagship product is its Enterprise Linux operating system.
It offers virtualization, data storage, application and cloud software for several platforms from mainframes to desktops.
Salesforce.com
A pioneer in selling software as a service, Salesforce started out by providing a single application – customer relationship management
(CRM) – through the cloud, cutting costs dramatically for its customers. Now it has moved vertically down the cloud stack offering
Force.com, a complete application platform, and Database.com, a cloud database platform. Salesforce is the market leader in cloud-based
CRM solutions, but in a big data market that is evolving rapidly its weakness is a lack of business intelligence tools – the heart of big data.
SAP
In the 1990s, SAP manufactured one of the world’s most successful enterprise resource management (ERP) systems. Since then it has
aggressively moved along the big data value chain. Through its acquisitions of Business Objects and Sybase it now has credible business
intelligence and database tools. HANA, its big data appliance, introduced in 2011 has been reasonably successful.
Tibco Software
Tibco provides middleware and software for data centre infrastructure. Its Spotfire product is a business intelligence tool that allows its
clients to link up to external databases or ERP systems and analyse the data within them in real time.
VMware
VMware is a leader in virtualisation and cloud platforms. Its flagship product is vSphere, a cloud-based virtualisation operating system. In
addition, the Spring Hadoop platform helps companies build big data engines. Its Cloud Foundry technology is an open platform to develop
new cloud applications. Its vFabric Data Director product provides databases as a service through the cloud. The company is about 80%
owned by EMC and often teams up with EMC and Cisco.



Cyber security companies
 Cyber-attacks remain the biggest investment risk faced by players in the big data space
 In the event that risk level rises, cyber security companies will benefit

Big data technology platforms are shifting from proprietary databases to ones based on open source database frameworks like Hadoop.
Open source software tends to be weak on security, partly because of the free-wheeling nature of many of the programmers who develop it.
The table below shows some of the security companies that should benefit from a higher perceived cyber security threat. In addition to
these companies, many of the big technology companies have strong security applications too: Microsoft has Security Essentials; Oracle
has Database Vault, IBM has Rational and Proventia; HP has Fortify and EMC has RSA.

Where do the internet security players sit in the Big Data value chain?
0 US$m 0
0 0 0
Check Point SoftwareSoftware (security) USA 12,035 18.3 1 Check Point Software develops software and hardware products and services for data secur
F5 Networks Software (internet infraUSA 10,696 29.8 1 1 1 F5 Networks provides Internet traffic management solutions for mission-critical IP servers an
Fortinet Software (security) USA 4,195 51.4 1 Fortinet provides network security solutions
F-Secure Software (security) Finland 353 14.7 1 F-Secure develops data security products for the mobile enterprise.
Qihoo 360 Software (security) China 2,989 36.5 1 Qihoo 360 Technology provides Internet and mobile security products in China
Sourcefire Software (security) USA 1,706 77.1 1 Sourcefire provides real-time network defence solutions.
Symantec Software (security) USA 12,123 10.3 1 Symantec provides security, storage and systems management solutions
Trend Micro Software (security) Japan 4,192 18.3 1 Trend Micro develops anti-virus computer software and internet security software.
Verint Systems Software (security) Israel 1,217 11.8 1 Verint Systems provides analytic software for interception, digital video security and surveill
Verisign Software (security) USA 6,615 22.5 1 VeriSign provides Internet infrastructure services needed by websites, enterprises, electroni
Websense Software (applications USA 776 13.2 1 Websense provides integrated web, data, and email security solutions that protect organiza




Telecom operators
 As more business-critical data flows through the cloud, telecom operators will gain more pricing power
 In many countries – especially on mobile networks – the data deluge will lead to bandwidth shortages
 Mobile operators are likely to be able to profit from a lucrative side-line in carrying time-sensitive business data, both in
the M2M market and in the cloud services market

Telecom operators are gearing up for a fight
Big data dramatically changes the demand and supply characteristics of the market for internet bandwidth. As we explained on page 4,
demand for internet bandwidth is growing at 35% per annum on fixed line networks and at 110% on mobile networks. The supply of
bandwidth, especially in the mobile sector, is not keeping pace, partly because there is little incentive for telecom operators to invest
heavily in high speed broadband networks. Price caps and net neutrality rules prevent them from charging internet companies the full cost
of the internet bandwidth they consume. As a result, Sync expects a mobile bandwidth crunch within the next couple of years.
A mobile bandwidth crunch is coming
Many operators aim to profit from big data
In addition to exploiting the short term bandwidth market disequilibrium created by the Global mobile data traffic (PB/month)
data deluge, many telecom operators see three additional ways to make money from big Global mobile broadband revenues ($bn)
data: first, by providing cloud services of their own; second, by encouraging the growth of 4,000 1,000
M2M revenue; and third by launching their own app stores. 3,500 900
800
3,000
700
2,500
In respect of cloud services, expect to see more M&A deals similar to Verizon’s $1.4bn 600
2,000 500
acquisition of Terremark. More operators are likely to expand into cloud-based enterprise 1,500 400
software services of their own. China Telecom, too, is building data centres across the 1,000
300
200
country that provide businesses a one-stop shop for their e-commerce needs. 500 100
‐ ‐
In respect of M2M revenues, a report earlier this year by Machina Research placed 2007 2008 2009 2010 2011 2012 2013 2014
Source: CM Research
Vodafone in top place for the global M2M market opportunity between now and 2020.
In respect of launching their own app stores, the results are likely to be hit and miss. The two big success stories so far appear to be SK
Telecom and China Mobile, but neither reported segmented results to allow us to assess their success in this space.



Other investment themes

Theme What does it mean? Our conclusions
Global How will TMT companies be On the way down, all TMT sectors will be hit indiscriminately. On the way up, Internet content, software and
slowdown impacted by a second global stock IT services will rally first
scenario market crash?
App revolution What does the explosion in apps Western traditional media stocks likely to do better than Asian ones. Software will see an app-fuelled, M&A
mean for the TMT sector? boom. Many cloud services companies will take off. Advertisers with a strong digital strategy will also
benefit.
Music, video Who will benefit from the rapid Music and video sites consume much Internet bandwidth but make little money. They are likely to suffer the
and social surge in music and video traffic on fate of Real Player at the hands of the larger social networks
networks the Internet?
Cyber security How will increased fears of cyber- Social networks and the big Internet champions are likely to face a higher threat level. Trade wars will
attacks impact the TMT sector? emerge in telecom equipment and semiconductors
Video games Are online and wireless games Online and wireless gaming revenues are growing much faster than console games. The app revolution
going to go through a boom should steepen their growth curve further
period?
Mobile When will mobile payments Telcos and credit card companies are investing heavily in NFC technology but are unlikely to see the main
payments become a mainstream investment benefit. Several small software companies are well positioned.
theme?
Chinese Should Chinese Internet China accounts for 11% of global IP traffic but only 6% of global IP advertising revenues. And Chinese
Internet companies be valued on the same Internet industry statistics are poorly policed
multiples as US companies?
Regulation What are the main regulatory The rules governing net neutrality, data privacy, online piracy and internet taxation are likely to change
issues that will impact TMT soon. Anti-trust probes against Apple and Google will intensify
companies in 2012?
Cloud If the cloud takes off, where will Companies addressing the three industry bottlenecks – data storage, cyber security and reliability – will
computing the highest returns be generated? benefit the most.



Our research approach

We study what’s new and what’s changing… the rest we leave to mainstream research

Our research approach:
Global Investment Technology, Media  Search for emerging technology trends
& Telecoms  Spot global investment themes
themes  Screen for local companies affected

Sector
Investment Thematic
Strategy Research

Our recent themes: Our research product:
App revolution, Chinese Internet, Big Data, Cloud  TMT sector outlook (bi-annual)
Computing, Cyber Security, Digital Media, HTML5,  In-depth thematic research (fortnightly)
LTE, Mobile Internet, Mobile Payments, Net  Technology briefings
Neutrality, Regulation, Smartphones, Social networks,  Analyst access
Video Games
 Bespoke research



Important disclosures
This document refers to industry trends in general. This document is provided for information purposes only and should not be regarded as
an offer, solicitation, invitation, inducement or recommendation relating to the subscription, purchase or sale of any security or other
financial instrument. This document does not constitute, and should not be interpreted as, investment advice.

About CM Research
CM Research is an independent research house based in London. We offer a subscription service covering the global technology, media
and telecom (TMT) sectors. Our clients include investors, corporations, consultancies and governments. We analyse emerging TMT trends
with a focus on disruptive technologies: how will they unfold; which industries will be impacted; and who will be the ultimate winners and
losers.

For our institutional investor clients, we convert these trends into global investment themes, highlighting local stocks that might be
impacted. Our aim is to help investors formulate a TMT investment strategy that is global, thematic, timely and coherent. For our corporate
clients, we convert these trends into global sector outlooks. Our aim is to help them stay one step ahead of the technology trends that are
shaping their industry.

At a time when many of our competitors have had their reputations mired by conflicts of interest, we fiercely guard our independence. Our
research is unbiased and free of any conflicts of interest. CM Research is a member of the European Association of Independent Research
Providers (EuroIRP) and is authorised and regulated by the Financial Services Authority.


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