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

www.researchcm.com 2

Contents WHATISBIGDATA?....................................................................................................................................3

GLOBALMARKETFORBIGDATA............................................................................................................4

BIGDATATRENDS.......................................................................................................................................6

WIDERTRENDSINTHECOMPUTINGSECTOR...................................................................................7

INTERNETCOMPANIES.............................................................................................................................13

DATASTORAGE,NETWORKINGANDHARDWARECOMPANIES................................................15

ENTERPRISESOFTWARECOMPANIES................................................................................................18

CYBERSECURITYCOMPANIES...............................................................................................................21

TELECOMOPERATORS.............................................................................................................................22

OTHERINVESTMENTTHEMES...............................................................................................................23

OURRESEARCHAPPROACH....................................................................................................................24

IMPORTANTDISCLOSURES.....................................................................................................................25

ABOUTCMRESEARCH...............................................................................................................................25



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

Big data is the next technology problem looking for a solution Today, there is a deluge of data on the internet. It comes from web crawlers (spiders), web robots (bots), web logs (blogs), emails, videos, tweet streams, genome sequences, traffic-flow sensor data, banking transactions, GPS trails and much more. This data, if properly interpreted can be used defensively to combat theft, fraud, cyber-attacks or terrorism; it can also be used commercially to target sales or provide business intelligence. So it is valuable to governments, banks, marketing agencies, social networks, retailers and business information providers. But there is a problem: it is so complex that it cannot be processed using conventional methods. The big money lies in developing the analytical engine that can intelligently interpret big data.

Defining big data Big data refers to any data that cannot be analysed by a traditional 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.

The digital unit scale

Source: CM Research

Big data’s characteristics make it difficult to analyse V3= High Volume, High Velocity and High Variety

Source: IBM

Unit Symbol SizeBit b 0 or 1Byte B 8 bitsKilobyte KB 1,000 BMegabyte MB 106 BGigabyte GB 109 BTerabyte TB 1012 BPetabyte PB 1015 BExabyte EB 1018 BZettabyte ZB 1021 BYottabyte YB 1024 B



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.

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

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%

Source: IDC, Cisco, CM Research

0

2

4

6

8

10

12

14

2006 2008 2010 2012 2014

Zettab

ytes

Total stored digital information in world

‐

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

2010 2011 2012 2013 2014 2015

PB/m

onth

Global IP traffic by type

VoIP

Online gaming

Video calling

Web, email

Internet video

File sharing

Business ‐

2,000

4,000

6,000

8,000

10,000

12,000

2011 2012 2013 2014 2015 2016

PB/m

onth

Global mobile data traffic by application type

Video

Data

File sharing

Other (M2M,gaming, VOIP)



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, raising the costs of analysis. This creates a highly lucrative market for analytical search engines that can interpret this unstructured data.

2. Open source: Proprietary database standards are giving way to new, open source big data technology platforms such as Hadoop. This means that barriers to entry may remain low for some time.

3. Cloud: Many corporations are opting to use cloud services to access big data analytical tools instead of building expensive data warehouses themselves. This implies that most of the money in big data will be made from selling hybrid cloud-based services rather than selling big databases.

4. M2M: In future, a growing proportion of big data will be generated from 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.

Structured vs. unstructured data Industry commentators normally classify big data into two categories: structured data 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.

Unstructured data is expensive to analyse Big data classification

Source: CM Research

Ease of use Classification Data type

DatabasesEasy and cheap to analyse XML data

Data warehousesEnterprise systems

Social mediaVoice, music & video

Difficult or expensive to analyse DocumentsEmail

RFIDGPS

Requires extensive infrastructure QRTemperature

Structured data

Unstructured data

Sensor data(machine‐to‐machine)



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 the main parts of the global technology sector – hardware, software and services – summarising how each will be impacted by the next generation of computing technology.

Watch list: The cloud generation will create a new set of winners along the computing value chain

Source: CM Research

HARDWARE SOFTWARE SERVICES

Databases Storage Servers Networking equipment

Operating systems

Analytics Security Cloud applications

Virtualisation IT services Data centres

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

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



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

away from relational databases (e.g. Oracle or SQL Server) to new database technologies such as NoSQL

Processing: new, distributed database platforms such as Hadoop are emerging, that can process semi-structured data far more cost-effectively than traditional database tools

Analytics: the value-add has

moved from databases to analytics – all the big database companies (IBM, SAP, Oracle) have been on an M&A spree, buying up business intelligence software houses such as Netezza 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

What does the big data supply chain look like?

Source: CM Research

Gather raw data on industrial scale Improve big data quality Commercialise big data

Big Data Production Big Data ConsumptionBig Data Management

Social mediaDocumentsDatabasesWeb crawlersWeb robots (bots)SensorsVoiceMusic & videoEmailRFIDCall recordsPayment detailsGPS

Volume

Variety

Velocity Big Data quality

Storage

Security

Databases

Analytics

Data Mining

Digital Marketing

Re‐selling

Search



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… The most popular database technology used today for capturing business data is the relational database management system (RDBMS), which was first created in the 1970’s.These relational databases are made by the likes of Oracle, IBM and Microsoft and use a computer language called SQL (Structured Query Language) to define, query and update the database.

… but these databases were not capable of handling big data… Over the last decade, business data has changed dramatically, creating two problems for traditional database makers: first the sheer size of the data has increased into the 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 problem, RDBMS platforms typically scaled up vertically, by adding more CPUs or more memory to the database management system. The second problem could not be dealt 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:

Oracle is the market leader in databases

Source: Company data, IDC, Gartner, CM Research

Oracle42%

IBM24%

Microsoft19%

SAP3%

Others12%

Database market share by revenues, 2011



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.

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.

Hadoop and NoSQL are now used by Oracle

Source: Oracle



ANALYTICS The lesson that Amazon, Google and Facebook all learnt early on in the digital age was that in order to build really fast big data engines you need all the ingredients to fit perfectly together – the servers, the databases, the networks, the analytical engines and the security. That’s why Google decided back in 2002 to build its big data analytical engines itself. Sometime afterwards, the leading players in big data – like IBM, Oracle, HP, EMC, Teradata – also came to this realisation. As the M&A chart on the following page demonstrates, each one of these industry leaders has been buying up the missing pieces in their portfolio of big data engine components. Over the last five years, Oracle, EMC, HP, IBM, Microsoft, SAP and Teradata have collectively spent more than $45bn on buying software, security or storage companies. The bulk of this money has gone on business intelligence tools such as Netezza, AsterData, Hyperion, Business Objects, SPSS and Cognos. Big data analytics is the new battleground in the technology sector. As databases become open sourced or commoditised, analytical engines will suck out most of the industry’s profits.

Business intelligence tools feature high in the target list for large technology companies The chart shows the transaction value (in $bn) of recent M&A deals in the big data technology space

2011 2010 2009 2008

Source: CM Research

0 1 2 3 4 5 6 7 8

IBM acquires Cognos (Data analysis software)Oracle acquires Hyperion (Data analysis software)

Microsoft acquires FAST Search and Transfer (Enterprise…Oracle acquires BEA Systems (Enterprise applications…Brocade Communications acquires Foundry Networks…

SAP acquires Business Objects (Data analysis software)Microsoft acquires Datallegro (Data analysis software)

EMC acquires Data Domain (Data storage)IBM acquires SPSS (Data analysis software)

SAP acquires Sybase (Data analysis software)Warburg Pincus acquires IDC (Information management)

IBM acquires Sterling Commerce (B2B software)Hexagon acquires Intergraph (Mapping software)

HP acquires 3Par (Data storage)IBM acquires Netezza (Data analysis software)Misys acquires Sophis (Application software)EMC acquires Isilon (Data storage software)

Attachmate acquires Novell (Intelligent workload…Oracle acquires Art Technology (CRM software)Verizon acquires Terremark (Cloud computing)

GGC Software acquires Lawson software (ERP software)Apax acquires Activant (ERP software)

Apax acquires Epicor Software (Enterprise software)CenturyLink acquires Savvis (Cloud computing)Ericson acquires Telcordia (Enterprise software)

Salesforce.com acquires Radian6 (Data analysis software)Dell acquires Force 10 Networks (Data centre networking)

Acer acquires iGware (Cloud computing)Teradata acquires Aster Data (Data analysis software)

IBM acquires Algorithmics (Risk management software for…Oracle acquires RightNow (Cloud computing)

SAP acquires Success Factors (Online HR software)



How does it all fit together? The diagramme opposite summarises how different technology industries feature in the big data value chain. What is interesting is that the big internet champions like Facebook and Google straddle the entire value chain: they collect data via their social network platforms, browsers and operating systems; they process it using their custom database systems; and they use it to target advertising dollars to customers likely to respond positively. They control the data and how it is used. So while many technology analysts point to IBM and Oracle as the big data champions, investors should keep an eye out for Amazon, Google, Facebook. Their analytical engines are hidden, but highly disruptive.

Where do the big players fit into the big data supply chain?

Source: CM Research

Big DataConsumption

Big DataManagement

Big DataProduction

Social networks

Cybersecurity

Telecom operators

Analytical engines

Search engines

Marketing agencies

Operating system and browser software developers

Cloud services providers

Apps developers

Data centres

Social mediaDocumentsDatabasesWeb crawlersWeb robots SensorsVoiceMusic & videoEmailRFIDCall recordsPayment detailsGPS

Third party resellers

Hardware makers

Data scientists



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?

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

Data management

Company Sector Country Mkt Cap P/E

Databases Analytics, applications

Storage, servers, networking

Security Consulting

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

Data production

Data consumption



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?

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

Data management




Security Consulting

Description

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.

Data production

Data consumption



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?


Data management




Security Consulting

Description

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.

Data production

Data consumption



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?


Data management




Security Consulting

Description

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

Data production

Data consumption



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.

Many operators aim to profit from big data In addition to exploiting the short term bandwidth market disequilibrium created by the data deluge, many telecom operators see three additional ways to make money from big data: first, by providing cloud services of their own; second, by encouraging the growth of M2M revenue; and third by launching their own app stores. In respect of cloud services, expect to see more M&A deals similar to Verizon’s $1.4bn acquisition of Terremark. More operators are likely to expand into cloud-based enterprise software services of their own. China Telecom, too, is building data centres across the country that provide businesses a one-stop shop for their e-commerce needs. In respect of M2M revenues, a report earlier this year by Machina Research placed 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.

A mobile bandwidth crunch is coming

Source: CM Research

‐ 100 200 300 400 500 600 700 800 900 1,000

‐ 500

1,000 1,500 2,000 2,500 3,000 3,500 4,000

2007 2008 2009 2010 2011 2012 2013 2014

Global mobile data traffic (PB/month)

Global mobile broadband revenues ($bn)



Other investment themes

Theme What does it mean? Our conclusions Global slowdown scenario

How will TMT companies be impacted by a second global stock market crash?

On the way down, all TMT sectors will be hit indiscriminately. On the way up, Internet content, software and IT services will rally first

App revolution What does the explosion in apps mean for the TMT sector?

Western traditional media stocks likely to do better than Asian ones. Software will see an app-fuelled, M&A boom. Many cloud services companies will take off. Advertisers with a strong digital strategy will also benefit.

Music, video and social networks

Who will benefit from the rapid surge in music and video traffic on the Internet?

Music and video sites consume much Internet bandwidth but make little money. They are likely to suffer the fate of Real Player at the hands of the larger social networks

Cyber security How will increased fears of cyber-attacks impact the TMT sector?

Social networks and the big Internet champions are likely to face a higher threat level. Trade wars will emerge in telecom equipment and semiconductors

Video games Are online and wireless games going to go through a boom period?

Online and wireless gaming revenues are growing much faster than console games. The app revolution should steepen their growth curve further

Mobile payments

When will mobile payments become a mainstream investment theme?

Telcos and credit card companies are investing heavily in NFC technology but are unlikely to see the main benefit. Several small software companies are well positioned.

Chinese Internet

Should Chinese Internet companies be valued on the same multiples as US companies?

China accounts for 11% of global IP traffic but only 6% of global IP advertising revenues. And Chinese Internet industry statistics are poorly policed

Regulation What are the main regulatory issues that will impact TMT companies in 2012?

The rules governing net neutrality, data privacy, online piracy and internet taxation are likely to change soon. Anti-trust probes against Apple and Google will intensify

Cloud computing

If the cloud takes off, where will the highest returns be generated?

Companies addressing the three industry bottlenecks – data storage, cyber security and reliability – will benefit the most.



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Our recent themes: App revolution, Chinese Internet, Big Data, Cloud Computing, Cyber Security, Digital Media, HTML5, LTE, Mobile Internet, Mobile Payments, Net Neutrality, Regulation, Smartphones, Social networks, Video Games

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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.