Cloud & Big Data

Date: April 1, 2012
Pages: 80
US$ 2,600.00
Publisher: IDATE Consulting & Research
Report type: Strategic Report
Delivery: E-mail Delivery (PDF)

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Cloud & Big Data
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.
  • 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?

1.1. Infrastructure-based challenges for the cloud
1.2. The cloudЎ¦s impact on the IT industry
1.3. The cloud: big data facilitator



3.1. The three types of cloud service
  3.1.1. IaaS: Infrastructure-as-a-Service
  3.1.2. PaaS: Platform-as-a-Service
  3.1.3. SaaS: Software-as-a-Service
  3.1.4. Weight of the different segments
3.2. Background
  3.2.1. Centralisation/decentralisation
  3.2.2. Emergence of ASPs: Application Service Providers
  3.2.3. Web services
  3.2.4. On-demand computing
3.3. Cloud architectures
  3.3.1. The private cloud
  3.3.2. The public cloud
  3.3.3. The hybrid cloud
3.4. Big data
  3.4.1. Structured and unstructured data
  3.4.2. Data mining
  3.4.3. Applications
  3.4.4. Technical requirements
  3.4.5. Processing the data
  3.4.6. Data sources
  3.4.7. Data analysis
  3.4.8. What cloud computing brings to big data


4.1. SOA: Service-Oriented Architecture
4.2. Broadband access
4.3. Virtualisation and multi-tenant solutions
  4.3.1. Virtualisation
  4.3.2. Multi-tenant architecture
4.4. Network fabrics
4.5. Big data technologies
  4.5.1. NoSQL
  4.5.2. MapReduce
  4.5.3. Hadoop
  4.5.4. BigTable and Google File System
  4.5.5. Cassandra and Dynamo
  4.5.6. Business Intelligence
4.6. Data centres
  4.6.1. Elements of a data centre
  4.6.2. Controlling energy costs
  4.6.3. Costs and key figures


5.1. Key developmental factors
  5.1.1. Software market dynamic and the switch to SaaS
  5.1.2. Flexibility, agility, interoperability
  5.1.3. Transforming CAPEX into OPEX and TCO
  5.1.4. Pay-as-you-go billing
  5.1.5. In-house expertise
  5.1.6. Consumer market developments
  5.1.7. Public authority involvement
  5.1.8. Big data development enablers
    Reusing data mining techniques
    Variety of data sources
    Business Intelligence
5.2. Critical developmental aspects
  5.2.1. Regulatory aspects
  5.2.2. Service Level Agreements and Quality of Service
    Service Level Agreement
    Quality of service
  5.2.3. Vertical integration and standardisation
    Standardisation initiatives
  5.2.4. Big data rollout constraints
    Computing capacities
    Software deployment


6.1. Industry structure
6.2. Player profiles
  6.2.1. Software publishers
    CA Technologies
  6.2.2. IaaS pure players
  6.2.3. Integrators
  6.2.4. Telcos
    Orange Business Services
    BT - Global Services
  6.2.5. Web hosting companies
    Telehouse - KDDI
  6.2.6. CDN operators
  6.2.7. The Internet giants
    Amazon Web Services


7.1. Data centre deployment issues
7.2. The development of big data
7.3. Public authoritiesЎ¦ role
7.4. TelcosЎ¦ potential
7.5. The cloud as value destroyer
7.6. Outlook for SaaS, PaaS and IaaS
7.7. Consumer cloud services


Table 1: Indicative price of data centre components (server and network)
Table 2: Average price of electricity in a selection of countries in 2011 (commercial rates)
Table 3: Average figures for the construction of a traditional data centre
Table 4: Top 10 software companies in 2010 in terms of software revenue
Table 5: Telehouse SLAs on cloud change/repair times
Table 6: Amazon S3 storage rates
Table 7: Types of cloud services sold by the different players in the marketplace
Table 8: Possible hosting locations for Microsoft cloud services
Table 9: Main cloud and big data products sold by Google Enterprise


Figure 2: The three types of cloud
Figure 3: Weight of the different cloud computing market segments in the European Union (EU-27), in 2011
Figure 4: The different cloud architectures
Figure 5: Stages in the data treatment process
Figure 6: The visible and invisible Web
Figure 7: Service-Oriented Architecture (SOA)
Figure 8: Virtualisation of two virtual machines
Figure 9: Workstation virtualisation
Figure 10: Multi-tenant architecture
Figure 11: Classic three-layer architecture
Figure 12: Fabric architecture
Figure 13: How MapReduce works
Figure 14: The components of Business Intelligence
Figure 15: A data centre
Figure 16: Evolution of PUE in Google data centres 2007-2010
Figure 17: Breakdown of data centre power consumption
Figure 18: Direct free cooling
Figure 19: Water-based cooling, reused to heat homes in Helsinki
Figure 20: A hot and cold aisle cooing system
Figure 21: Two examples of container data centre, from HP and Sun
Figure 22: Growth of the global software/IT service market, 2008-2014
Figure 23: Comparison of CAPEX - OPEX in terms of capacity
Figure 24: CAPEX vs. OPEX TCO
Figure 25: Price of OVH miniCloud services
Figure 26: AppleЎ¦s iCloud solution for sharing and storing files
Figure 27: Google Apps for consumers and businesses
Figure 28: Examples of Microsoft SLAs for its Azure service (at bottom: monthly availability)
Figure 29: Cloud computing and big data industry structure
Figure 30: Excel file created and shared online using Office
Figure 312: Sales Cloud CRM service interface
Figure 32: Distribution of GoGrid data centres around the world
Figure 33: Distribution of BT data centres
Figure 34: AkamaiЎ¦s cloud offering
Figure 35: Growth of cloud servicesЎ¦ share of total revenue
Figure 36: The Limelight suite of services
Figure 37: Location of Google data centres in the United States and around the world (2008)
Figure 38: Growth of the IT services and software markets in Europe (EU-27)

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