Cloud & Big Data: The rise of the Data Centre

May 31, 2012 Off By David
Grazed from PR NewsWire.  Author: PR Announcement.

Reportlinker.com announces that a new market research report is available in its catalogue:

Cloud & big data: The rise of the data centre

http://www.reportlinker.com/p0874140/Cloud–big-data-The-rise-of-the-dat…

This report explores the various technical and economic issues bound up with cloud computing and Big Data – giving readers a deeper understanding of these concepts that are the subject of so much talk today. Among the key points examined is the critical role that data centres play when implementing technical solutions. Readers will also get a detailed profile of the players, both public and private sector, who are shaping the market…

Key questions

• What are the main technological components of cloud computing and Big Data?

• Is the data centre key for both?

•What are the main challenges in setting up a data centre?

• What are the key developmental issues and critical aspects in the development of Big Data and cloud computing?

• What role are public actors playing in the development of these two concepts? What regulatory provisos are in play?

• IaaS, SaaS, PaaS: who are the target customers for these services? Do they create added value to software and infrastructure markets?

• Big Data: evolution or revolution? What outlook for the coming years? • Who are the main cloud computing and Big Data players?

Table of contents

1. Executive Summary 8

1.1. Infrastructure-based challenges for the cloud .9

1.2. The cloud’s impact on the IT industry9

1.3. The cloud: big data facilitator 10

2. Methodology 12

3. Main concepts . 14

3.1. The three types of cloud service .14

3.1.1. IaaS: Infrastructure-as-a-Service15

3.1.2. PaaS: Platform-as-a-Service16

3.1.3. SaaS: Software-as-a-Service .16

3.1.4. Weight of the different segments 16

3.2. Background .17

3.2.1. Centralisation/decentralisation .17

3.2.2. Emergence of ASPs: Application Service Providers.17

3.2.3. Web services17

3.2.4. On-demand computing.18

3.3. Cloud architectures .18

3.3.1. The private cloud18

3.3.2. The public cloud .19

3.3.3. The hybrid cloud.19

3.4. Big data.20

3.4.1. Structured and unstructured data .20

3.4.2. Data mining 21

3.4.3. Applications 21

3.4.4. Technical requirements 22

3.4.5. Processing the data22

3.4.6. Data sources 23

3.4.7. Data analysis24

3.4.8. What cloud computing brings to big data24

4. Key technologies 25

4.1. SOA: Service-Oriented Architecture25

4.2. Broadband access.26

4.3. Virtualisation and multi-tenant solutions27

4.3.1. Virtualisation.27

4.3.2. Multi-tenant architecture.28

4.4. Network fabrics .29

4.5. Big data technologies 31

4.5.1. NoSQL31

4.5.2. MapReduce31

4.5.3. Hadoop.32

4.5.4. BigTable and Google File System32

4.5.5. Cassandra and Dynamo.33

4.5.6. Business Intelligence33

Cloud & Big Data

www.idate.org © IDATE 2012 4

4.6. Data centres35

4.6.1. Elements of a data centre.35

4.6.2. Controlling energy costs .36

4.6.3. Costs and key Figures.41

5. Key developmental factors & critical aspects 42

5.1. Key developmental factors 42

5.1.1. Software market dynamic and the switch to SaaS .42

5.1.2. Flexibility, agility, interoperability 43

5.1.3. Transforming CAPEX into OPEX and TCO44

5.1.4. Pay-as-you-go billing46

5.1.5. In-house expertise47

5.1.6. Consumer market developments47

5.1.7. Public authority involvement.49

5.1.8. Big data development enablers 50

Reusing data mining techniques.50

Variety of data sources .51

Business Intelligence 51

5.2. Critical developmental aspects51

5.2.1. Regulatory aspects.51

5.2.2. Service Level Agreements and Quality of Service53

Service Level Agreement53

Quality of service 54

5.2.3. Vertical integration and standardisation .54

Verticalisation .54

Standardisation.54

Standardisation initiatives .55

5.2.4. Big data rollout constraints .55

Computing capacities55

Software deployment 56

6. Industry organisation and structure . 57

6.1. Industry structure.57

6.2. Player profiles .58

6.2.1. Software publishers59

Microsoft .59

Salesforce.com.61

 

CA Technologies 62

6.2.2. IaaS pure players .63

GoGrid 63

6.2.3. Integrators 64

IBM .64

Cisco.65

EMC66

6.2.4. Telcos.67

Orange Business Services67

BT – Global Services 68

6.2.5. Web hosting companies .69

OVH69

Telehouse – KDDI 70

Rackspace71

6.2.6. CDN operators .72

Akamai72

Limelight .73

6.2.7. The Internet giants .74

Google 74

Amazon Web Services76

Apple.77

7. Strategic analysis 78

7.1. Data centre deployment issues .78

7.2. The development of big data.78

7.3. Public authorities’ role .79

7.4. Telcos’ potential 79

7.5. The cloud as value destroyer 80

7.6. Outlook for SaaS, PaaS and IaaS.81

7.7. Consumer cloud services 81

Tables

Table 1: Indicative price of data centre components (server and network) .41

Table 2: Average price of electricity in a selection of countries in 2011 (commercial rates) .41

Table 3: Average Figures for the construction of a traditional data centre .41

Table 4: Top 10 software companies in 2010 in terms of software revenue .43

Table 5: Telehouse SLAs on cloud change/repair times.44

Table 6: Amazon S3 storage rates .47

Table 7: Types of cloud services sold by the different players in the marketplace .58

Table 8: Possible hosting locations for Microsoft cloud services 59

Table 9: Main cloud and big data products sold by Google Enterprise .75

Figures

Figure 2: The three types of cloud .15

Figure 3: Weight of the different cloud computing market segments in the European Union (EU-

27), in 2011.16

Figure 4: The different cloud architectures.20

Figure 5: Stages in the data treatment process .22

Figure 6: The visible and invisible Web24

Figure 7: Service-Oriented Architecture (SOA)25

Figure 8: Virtualisation of two virtual machines27

Figure 9: Workstation virtualisation27

Figure 10: Multi-tenant architecture .29

Figure 11: Classic three-layer architecture 30

Figure 12: Fabric architecture 30

Figure 13: How MapReduce works 32

Figure 14: The components of Business Intelligence.34

Figure 15: A data centre 35

Figure 16: Evolution of PUE in Google data centres 2007-201037

Figure 17: Breakdown of data centre power consumption .37

Figure 18: Direct free cooling.38

Figure 19: Water-based cooling, reused to heat homes in Helsinki .39

Figure 20: A hot and cold aisle cooing system.39

Figure 21: Two examples of container data centre, from HP and Sun.40

Figure 22: Growth of the global software/IT service market, 2008-201442

Figure 23: Comparison of CAPEX – OPEX in terms of capacity45

Figure 24: CAPEX vs. OPEX TCO.45

Figure 25: Price of OVH miniCloud services46

Figure 26: Apple’s iCloud solution for sharing and storing files48

Figure 27: Google Apps for consumers and businesses48

Figure 28: Examples of Microsoft SLAs for its Azure service (at bottom: monthly availability) 53

Figure 29: Cloud computing and big data industry structure57

Figure 30: Excel file created and shared online using Office 365 60

Figure 312: Sales Cloud CRM service interface 61

Figure 32: Distribution of GoGrid data centres around the world .63

Figure 33: Distribution of BT data centres68

Figure 34: Akamai’s cloud offering.72

Figure 35: Growth of cloud services’ share of total revenue 73

Figure 36: The Limelight suite of services74

Figure 37: Location of Google data centres in the United States and around the world (2008) 75

Figure 38: Growth of the IT services and software markets in Europe (EU-27) .80

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