2. Hyperscale Datacenters Market Shares and Forecasts
2.1 Hyperscale Data Center Scale and Automation
2.1.1 Cloud 2.0 Mega Data Center Fabric Implementation
2.1.2 Cloud 2.0 Mega Data Center Different from the Hyperscale Cloud
2.1.3 Cloud 2.0 Mega Data Center Automatic Rules and Push-Button Actions
2.1.4 Making Individual Circuits And Devices Unimportant Is A Primary Aim Of Fabric Architecture
2.1.5 Digital Data Expanding Exponentially, Global IP Traffic Passes Zettabyte (1000 Exabytes) Threshold
2.1.6 Google Kubernetes Open Source Container Control System
2.1.7 Google Kubernetes Defacto Standard Container Management System
2.1.8 Google Shift from Bare Metal To Container Controllers
2.1.9 Cloud 2.0 Mega Data Center Market Driving Forces
2.2 Hyperscale Data Center Market Shares
2.2.1 Cloud Datacenter, Co-Location, and Social Media Cloud, Revenue Market Shares, Dollars, Worldwide, 2016
2.2.2 Cloud 2.0 Mega Datacenter Cap Ex Spending Market Shares Dollars, Worldwide, 2016
2.2.3 Amazon Capex for Cloud 2.0 Mega Data Centers
2.2.4 Amazon (AWS) Cloud
2.2.5 Amazon Datacenter Footprint
2.2.6 Cloud 2.0 Mega Data Center Social Media and Search Revenue Market Shares, Dollars, 2016
2.2.7 Top Hyperscale Companies
2.2.8 Biggest Data Centers
2.2.9 Microsoft Azure
2.2.10 Microsoft Data Center, Dublin, 550,000 Sf
2.2.11 Microsoft Data Center Container Area in Chicago.
2.2.12 Microsoft Quincy Data Centers, 470,000 Square Feet
2.2.13 Microsoft San Antonio Data Center, 470,000 SF
2.2.14 Microsoft 3rd Data Center in Bexar Could Employ 150
2.2.15 Microsoft Builds the Intelligent Cloud Platform
2.2.16 Microsoft's datacenter footprint
2.2.17 Google Datacenter Footprint
2.2.18 Apple Datacenter Footprint
2.2.19 Facebook Datacenter Footprint
2.2.20 Chef Web-Scale Automation Of Systems Integration In The Cloud
2.2.21 Docker Open Platform
2.2.22 OpenStack
2.2.23 Ragingwire
2.2.24 Simplifying Messaging is a Priority for Goldman Sachs Implementing Automation
2.2.25 IBM
2.3 Cloud 2.0 Mega Data Center Market Forecasts
2.3.1 Market Segments: Web Social Media, Web Wireless Apps, Enterprise / Business Transactions, Co-Location, And Broadcast / Communications
2.3.2 Cloud 2.0 Mega Data Center Is Changing The Hardware And Data Center Markets
2.4 Hyperscale Data Center Storage Market Analysis
2.5 Mega-Datacenter: Internet Giants Continue To Increase Capex
2.6 Cloud 2.0 Mega Data Center Size
2.6.1 Cloud 2.0 Mega Data Centers
2.6.2 Public Cloud Infrastructure
2.7 Multi-Tenant Data Center Market Shares and Revenue Forecasts
2.7.1 Colocation Providers
2.7.2 Carrier-Neutral Colocation Providers
2.7.3 Wholesale Data Center Providers
2.7.4 Largest Data Centers
2.8 Cloud 2.0 Mega Data Center
2.8.1 Cloud 2.0 Mega Data Center Is Changing The Hardware And Data Center Markets
2.8.2 Storage SATA Drives Meet Mega Data Center Requirements
2.8.1 Data Center Switching
2.8.2 ASIC Switch Vendors
2.8.3 Data Center Rack Market
2.9 Hyperscale Datacenter Future
2.9.1 Public Cloud Services Revenue
2.10 Edge Cloud Data Centers
2.10.1 Edge Data Center Definition
2.11 Data Expanding And Tools Used To Share, Store And Analyze Evolving At Phenomenal Rates
2.11.1 Video Traffic
2.11.2 Cisco Analysis of Business IP Traffic
2.11.3 Increasing Video Definition: By 2020, More Than 40 Percent of Connected Flat-Panel TV Sets Will Be 4K
2.11.4 M2M Applications
2.11.5 Applications, For Telemedicine And Smart Car Navigation Systems, Require Greater Bandwidth And Lower Latency
2.11.6 Explosion of Data Inside Cloud 2.0 Mega Data Center with Multi- Threading
2.11.7 Cloud 2.0 Mega Data Center Multi-Threading Automates Systems Integration
2.11.8 Fixed Broadband Speeds (in Mbps), 2015-2020
2.11.9 Internet Traffic Trends
2.11.10 Internet of Things
2.11.11 The Rise of the Converged “Digital Enterprise”
2.11.12 Enterprise Data Centers Give Way to Commercial Data Centers
2.12 Hyperscale Data Center TCO and Pricing: Server vs. Mainframe vs. Cloud vs. Cloud 2.0
2.12.1 Labor Accounts For 75% Of The Cost Of An Enterprise Web Server Center
2.12.2 Cloud 2.0 Systems And The Mainframe Computing Systems Compared
2.12.3 Cloud 2.0 and Mainframe Implements Shared Resource
2.12.4 Average Operating Density Of Data Centers
2.12.5 Mainframe Capacity vs. Cloud 2.0
2.12.6 Enterprise IT Departments TCO / ROI Custom Data Center Cost Analysis
2.12.7 Server, Mainframe, Cloud, and Cloud 2.0 Cost Comparisons
2.12.8 Server to MIPS Conversion Calculations
2.12.9 Mainframe Updates And Cost Efficiencies
2.12.10 Cost of Cloud Computing
2.12.11 Types of Cloud Computing
2.12.12 Software-Defined Infrastructure
2.12.13 Scale
2.13 Cloud Hyperscale Data Center Regional Market Analysis
2.13.1 US Data Center REITs
2.13.2 Chicago Data Center Supply Grows
2.13.3 Digital Realty Trust Largest Data Center: Cermak, Chicago, 1.1 Million Square Feet
2.13.4 US Data Center Activity
2.13.5 Cloud Demand Globally
2.13.6 Landlords Adapt to Cloud Globally
2.13.7 Amazon, Google Detail Next Round of Cloud Data Center Launches
2.13.8 Cloud Data Centers Market in Europe
2.13.9 Cloud Data Centers Market in Ireland
2.13.10 Japanese Data Centers
3. Hyperscale Datacenter Infrastructure Description
3.1 Amazon Cloud
3.1.1 Amazon AWS Regions and Availability Zones
3.1.2 Amazon Addresses Enterprise Cloud Market, Partnering With VMware
3.1.3 AWS Achieves High Availability Through Multiple Availability Zones
3.1.4 AWS Improving Continuity Replication Between Regions
3.1.5 Amazon (AWS) Meeting Compliance and Data Residency Requirements
3.1.6 AWS Step Functions Software
3.1.7 Amazon QuickSight Software
3.1.8 Amazon North America
3.1.9 AWS Server Scale
3.1.10 AWS Network Scale
3.2 Facebook
3.2.1 Dupont Fabros Constructing Second Phase In Acc7 Represents An Expanded Relationship with Facebook
3.2.2 Facebook $1B Cloud 2.0 Mega Data Center in Texas
3.2.3 Facebook $300 Million Cloud 2.0 Mega Data Center in Iowa
3.2.4 Fort Worth Facebook Mega-Data Center
3.2.5 Facebook Forest City, N.C. Cloud 2.0 mega data center
3.2.6 Data Center Fabric, The Next-Generation Facebook Data Center Network
3.2.7 Facebook Altoona Data Center Networking Fabric
3.2.8 Facebook Clusters and Limits Of Clusters
3.2.9 Facebook Fabric
3.2.10 Facebook Network Technology
3.2.11 Facebook Fabric Gradual Scalability
3.2.12 Facebook Mega Datacenter Physical Infrastructure
3.2.13 Facebook Large Fabric Network Automation
3.2.14 Facebook Fabric Data Center Transparent Transition
3.2.15 Facebook Large-Scale Network
3.3 Google Meta Data Centers
3.3.1 Google Datacenter Network
3.3.2 Google Office Productivity Dynamic Architecture
3.3.3 Google Search Engine Dynamic Architecture
3.3.4 Big Files
3.3.5 Repository
3.3.6 Google Clos Networks
3.3.7 Google B4 Datacenter WAN, a SDN
3.3.8 Google Programmable Access To Network Stack
3.3.9 Google Compute Engine Load Balancing
3.3.10 Google Compute Engine (GCE) TCP Stream Performance Improvements
3.3.11 Google The Dalles, Oregon Cloud 2.0 Mega Data Center
3.3.12 Lenoir, North Carolina
3.3.13 Google Hamina, Finland
3.3.14 Google Mayes County
3.3.15 Google Douglas County
3.3.16 Google Cloud 2.0 Mega Data Center St Ghislain, Belgium
3.3.17 Google Council Bluffs, Iowa Cloud 2.0 Mega Data Center
3.3.18 Google Douglas County Cloud 2.0 Mega Data Center
3.3.19 Google $300m Expansion of Existing Metro Atlanta Data Center
3.3.20 Google B4 SDN Initiative Benefits: Not Need To Be A Network Engineer To Control A Network; Can Do It At An Application Level
3.3.21 Google Cloud 2.0 Mega Data Center in Finland
3.3.22 Google Switches Provide Scale-Out: Server And Storage Expansion
3.3.23 Google and Microsoft 25G Ethernet Consortium
3.3.24 Google Workload Definitions
3.3.25 Google Kubernetes Container
3.3.26 Google Optical Networking
3.3.27 Google Data Center Efficiency Measurements
3.3.28 Google Measuring and Improving Energy Use
3.3.29 Google Comprehensive Approach to Measuring PUE
3.3.30 Q3 2016 PUE Performance
3.4 Baidu
3.4.1 Baidu Data Center, Shanxi
3.4.2 China Mobile Working With Leading Chinese Language Search Engine Baidu And Schneider Electric
3.5 China Mobile
3.6 Tencent
3.6.1 Tencent $1 Billion Midwest China Data Center
3.6.2 Tencent Facilitates Cloud
3.7 Smart City Data Center Comes Online
3.7.1 SNIA China Big Data Project
3.8 Alibaba
3.9 Yahoo
3.10 Microsoft
3.10.1 Microsoft .Net Dynamically Defines Reusable Modules
3.10.2 Microsoft Combines Managed Modules into Assemblies
3.10.3 Microsoft Architecture Dynamic Modular Processing
3.10.4 Microsoft Builds Azure Cloud Data Centers in Canada
3.10.5 Microsoft Dublin Cloud 2.0 mega data center
3.10.6 Microsoft Data Center Largest in U.S.
3.10.7 Microsoft Crafts Homegrown Linux For Azure Switches
3.10.8 Microsoft Azure Cloud Switch
3.10.9 Microsoft Azure CTO Cloud Building
3.10.10 Microsoft Cloud 2.0 Mega Data Center Multi-Tenant Containers
3.10.11 Microsoft Managed Clustering and Container Management: Docker and Mesos
3.10.12 Kubernetes From Google or Mesos
3.10.13 Microsoft Second Generation Open Cloud Servers
3.10.14 Azure Active Directory
3.10.15 Microsoft Azure Stack Platform Brings The Suite Of Azure Services To The Corporate Datacenter
3.10.16 Hardware Foundation For Microsoft Azure Stack
3.11 Apple
3.11.1 Apple Invests €1.7 Billion in European Data Centres
3.11.2 Apple Builds $2 Billion Cloud 2.0 mega data center in Arizona
3.12 Goldman Sachs
3.12.1 Simplifying Messaging is a Priority for Goldman Sachs
3.12.2 Goldman Sachs Cloud 2.0 Mega Data Center
3.12.3 Goldman Sachs Security for The Financial Services Organization
3.12.4 Goldman Sachs: Containers Have Real Promise at The Institution
3.12.5 Goldman Sachs Cloud Computing
3.13 Fidelity Investments
3.13.1 Fidelity Investments Core Unit Building Blocks
3.13.2 Fidelity Centercore Design
3.13.3 Fidelity Ties Into Modular Momentum Among Financials
3.14 QTS Custom Data Centers
3.14.1 QTS Multi Tenant Data Center
3.14.2 QTS Critical Facilities Management
3.15 IBM
3.15.4 Linux-Based Solutions Under IBM z/VM® Shared Infrastructure Support Hybrid Workloads
3.15.5 IBM Cloud Managed Services on z Systems
3.15.6 IBM Builds a Cloud 2.0 mega data center in India
3.15.7 IBM Outsourcing
3.15.8 IBM Server SAN Software-Led Infrastructure
3.15.9 IBM Partnership with American Airlines
3.15.10 IBM Cloud Momentum In The Airlines Industry
3.15.11 IBM CICS
3.15.12 IBM z13 Mainframe Hardware Platform
3.15.13 IBM z13 Software Compression Algorithm In Db/2 Cuts The Number Of Bits Required To Store Data From 80 Bits To Four Bits
3.16 DuPont Fabros Technology
3.16.1 Data Center Market Trends For Wholesale Commissioned MW Trend
3.17 Hewlett Packard
3.17.1 HP Hyperscale Composable Infrastructure
3.17.2 HP Data Center Control Human Tools With Point And Click Interfaces
3.17.3 HP Data Center Hyperscaler Control
3.17.4 Hewlett Packard Project Synergy Composable Infrastructure Initiative
3.18 NTT Raging Wire
3.19 Rackspace
3.19.1 Rackspace Power
3.19.2 Rackspace Network
3.20 Equinix
3.20.1 HK3 Hong Kong - Data Center
3.20.2 Equinox Supports Diverse And Rapidly Growing International Business Clusters, Rich Industry Ecosystem
3.20.3 Equinox Dublin Metro Facilities
3.20.4 Equinix Brings Online Sixth London Data Center
3.20.5 Equinix Performance Hub
3.21 Twitter
3.22 Bank of America
3.23 Wells Fargo
3.24 eBay
3.25 Switch SuperNAP
3.25.1 Switch International Expansion
3.25.2 Switch Cloud Connectivity Charges Lowered
3.25.3 Switch SUPERNAP High Density Designs
3.25.4 Red Hat Ansible
3.25.5 Red Hat Ansible Architecture, Agents, And Security
3.25.6 Red Hat Ansible Advanced Features
3.25.7 Red Hat / Ansible
3.26 Cisco
4. Hyperscale Datacenters Research and Technology
4.1 Enterprise IT Control Centers
4.2 Open Compute Project (OCP),
4.2.1 Microsoft Investment in Open Compute
4.2.2 Microsoft Leverages Open Compute Project to Bring Benefit to Enterprise Customers
4.3 Open Source Foundation
4.3.1 OSPF Neighbor Relationship Over Layer 3 MPLS VPN
4.4 Equinix Expansion of LD6 International Business Exchange Datacenter
4.4.1 Equinix and Oracle Collaborate to Bring Oracle Cloud Services to Equinix Cloud Exchange in Six Global Markets
4.4.2 Oracle Cloud Platform 562
4.5 Power Management
4.6 M2M Industry
4.7 Equinix Cloud Exchange Interconnection Solution
4.8 System On A Chip (SoCs) for Cloud 2.0 Mega Data Centers
4.8.1 A New Class of Low-Power Server SoCs
4.8.2 Re-Architecting the Network: Software Defined Networks (SDNs)
4.8.3 Synopsys SoCs
4.8.4 Open Network Foundation (ONF) Addresses Need For SoC Lower Power Consumption
4.9 Dynamic Systems
4.9.1 Robust, Enterprise-Quality Fault Tolerance
4.10 Cache / Queue
4.11 Multicast
4.12 Performance Optimization
4.13 Fault Tolerance
4.13.1 Gateways
4.13.2 Promise Of Web Services
4.14 IP Addressing And Directory Management
4.14.1 Dynamic Visual Representations
4.14.2 Application Integration
4.14.3 Point Applications
4.14.4 Fault Tolerance and Redundancy Solutions
4.14.5 Goldman Sachs Open Compute Project
4.15 Robust, Quality Cloud Computing
4.16 Networking Performance
4.17 Data Center Bandwidth Pricing:
5. Hyperscale Datacenters Company Profiles
5.1 365 Data Centers
5.2 Amazon
5.2.1 Amazon Business
5.2.2 Amazon Competition
5.2.3 Amazon Description
5.2.4 Amazon Revenue
5.3 Apple
5.3.1 Apple / AuthenTec
5.3.2 Authentec Revenue Recognition - Smart Sensors
5.3.3 Apple
5.3.4 Apple Business Strategy
5.3.5 Apple Products
5.3.6 Apple iPhone
5.3.7 Apple Mac Hardware Products
5.3.8 Apple iPod
5.3.9 Apple iTunes®
5.3.10 Apple Mac App Store
5.3.11 Apple iCloud
5.3.12 Apple Software Products and Computer Technologies
5.3.13 Apple Operating System Software iOS
5.3.14 Apple Mac OS X
5.3.15 Apple Third-Largest Mobile Phone Maker
5.3.16 Apple Revenue
5.3.17 Apple Regional Segment Operating Performance
5.3.18 Apple Net Sales
5.3.19 Apple iPhone Shipments
5.3.20 Apple iPad Shipments
5.3.21 Apple Revenue
5.4 Alibaba
5.4.1 Alibaba Cloud Expands Data Centers, Steps Up Challenge to Amazon, Microsoft
5.4.2 Alibaba Cloud Unit has 2.3 Million Customers
5.4.3 Alibaba Seeks To Leverage Applications Integration via Automated Cloud Processes
5.4.4 Alibaba Cloud Middle East
5.4.5 Alibaba Cloud Europe
5.4.6 Alibaba Cloud Australia
5.4.7 Alibaba Cloud Japan
5.5 Baidu
5.5.1 Baidu Platform
5.5.2 Baidu Mobile Era Cloud, Mobile Search
5.5.3 Baidu, The Largest Chinese Search Engine
5.5.4 Baidu Self-Designed 10Gb TOR Switch
5.5.5 Baidu ARM on a Large Scale
5.5.6 Baidu Self-Designed SSD
5.5.7 Baidu Customized Rack Servers
5.5.8 Baidu Buys Modular Data Center From Schneider
5.6 Chef
5.6.1 Chef Customers
5.6.1 Chef Partner Ecosystem Includes AWS, Dell, and Rackspace
5.6.2 Chef Compliance, Workflow, and Automation Support
5.6.3 Chef Professional DevOps Practice Service Partners
5.6.4 Chef Technology Partners Build World-Class Integrations with Chef
5.6.5 Chef Value Added Resellers
5.7 China Building A Cloud Computing Complex
5.8 China Mobile
5.9 Colocation America Data Center Bandwidth and Measurements
5.10 Colo-D
5.10.1 Colo-D Strong Growth Opening Of A Second Cloud 2.0 mega data center In Quebec In 2016
5.11 CoreSIte
5.11.1 CoreSite Cloud Data Center Leasing Accelerates
5.11.2 Key Markets Update
5.12 CyrusOne
5.13 Digital Realty
5.14 Docker
5.15 DuPont Fabros Technology
5.15.1 DuPont Fabros Technology Customer Analysis
5.15.2 DuPont Fabros Operating Portfolio: Tier 1 Markets
5.16 Edge ConneX
5.16.1 EdgeConneX Hyperscale Cloud Anchor
5.16.2 EdgeConneX Disrupts Incumbent Data Center Providers
5.16.3 EdgeConneX ‘Disruptive Network Positioning
5.16.4 EdgeConneX - US Strategy
5.16.5 Edge Data Center Providers Changing the Internet’s Geography
5.16.6 EdgeConneX Building at the Internet Edge
5.16.7 EdgeConneX Demand Dynamics
5.16.8 EdgeConneX Funding
5.16.9 EdgeConneX Software Supports Speed to Market
5.16.10 EdgeConneX Cloud Strategy
5.16.11 EdgeConneX in Europe
5.16.12 Liberty Global Anchor Tenant in London
5.17 Equinix
5.17.1 EQUINIX, INC. Revenues
5.17.2 Equinix Purchase of Digital Realty Trust
5.17.3 Equinix Acquisition of TelecityGroup
5.18 Facebook
5.18.1 Facebook Technology
5.18.2 Facebook Sales and Operations
5.18.3 Facebook Management Discussion
5.18.4 Facebook Revenue
5.18.5 Facebook
5.18.6 Facebook App Draining Smart Phone Batteries
5.18.7 Facebook Messaging Provides Access to User Behavioral Data
5.18.8 Facebook Creating Better Ads
5.18.9 Facebook Next Generation Services
5.18.10 Facebook Platform
5.18.11 Facebook Free Basics
5.18.12 Facebook AI
5.18.13 Facebook Revenue
5.18.14 Facebook Revenue Growth Priorities:
5.18.15 Facebook Average Revenue Per User ARPU
5.18.16 Facebook Geographical Information
5.18.17 Facebook WhatsApp
5.18.18 Facebook WhatsApp Focusing on Growth
5.19 Forsythe
5.19.1 Forsythe Data Centers An Adaptable Facility to Meet Clients’ Evolving Needs
5.19.2 Forsythe Data Centers All-Encompassing Network
5.20 Google
5.20.1 Google Revenue
5.20.2 Google
5.20.3 Google Search Technology
5.20.4 Google Recognizes World Is Increasingly Mobile
5.20.5 Google Nest
5.20.6 Google / Nest Protect
5.20.7 Google / Nest Safety History
5.20.8 Google / Nest Learning Thermostat
5.20.9 Google Chromecast
5.21 Hewlett Packard Enterprise 727
5.22 IBM
5.22.1 IBM Strategy
5.22.2 IBM Cloud Computing
5.22.3 IBM Business Model
5.22.4 IBM Solutions
5.22.5 IBM Blockchain
5.22.6 IBM PureData System for Transaction Analysis
5.22.7 IBM Business Partners
5.22.8 IBM Messaging Extension for Web Application Pattern
5.22.9 IBM MobileFirst
5.22.10 IBM Business Analytics and Optimization Strategy
5.22.11 IBM Growth Market Initiatives
5.22.12 IBM Business Analytics and Optimization
5.22.13 IBM Strategy Addresses Volatility of Information Technology (IT) Systems
5.22.14 IBM Smarter Planet
5.22.15 IBM Business Revenue Segments And Capabilities
5.22.16 IBM Software Capabilities
5.23 Intel
5.23.1 Intel Business
5.23.2 Intel Company Strategy
5.23.3 Intel In The Internet Of Things Market Segment
5.23.4 Intel Competitive Advantages
5.24 I/O
5.25 InterXion
5.25.1 Interxion Revenue
5.26 Mesosphere
5.26.1 Modern App Platform Services
5.26.2 Mesosphere Enterprise DC/OS Hybrid cloud independence
5.26.3 Mesosphere / Open Source Mesos Tool
5.26.4 Modern Enterprise Applications Use Of Open Source Software
5.26.5 Banding Together To Deliver Mesosphere Containers And Stateful DC/OS
5.26.6 Mesosphere DC/OS: Mesos
5.26.7 Heart of DC/OS Mesos
5.26.8 DC/OS Implements Containers
5.26.9 DC/OS Available Services as Packages Included in Universe
5.26.10 Mesosphere Customers
5.27 Microsoft
5.27.1 Microsoft Builds the Intelligent Cloud Platform
5.27.2 Microsoft Targets Personal Computing
5.27.3 Microsoft Reportable Segments
5.27.4 Skype and Microsoft
5.27.5 Microsoft / Skype / GroupMe Free Group Messaging
5.27.6 Microsoft SOA
5.27.7 Microsoft .Net Open Source
5.27.8 Microsoft Competition
5.27.9 Microsoft Revenue
5.28 US National Security Agency 784
5.29 NEC
5.29.1 NEC Revenue
5.29.2 NEC Leading Company In Small Cell Solutions
5.29.3 NEC Business Outline
5.30 NTT / RagingWire
5.30.1 RagingWire Data Centers
5.30.2 RagingWire Best Practice Approach to Data Center Colocation
5.30.3 RagingWire Joined NTT
5.31 OpenStack Cloud Controller
5.31.1 OpenStack Has Created Its Own APIs
5.31.2 How Many Openstack Clouds Have Been Deployed
5.31.3 OpenStack Functions
5.31.4 OpenStack Regional Market
5.31.5 OpenStack Collaboration with Industry
5.31.6 OpenStack Cloud Service Context
5.31.7 OpenStack Industry Presence
5.31.8 Storage Innovations Drive OpenStack
5.32 Puppet
5.32.1 Puppet: Standard platform
5.32.2 Puppet Customers
5.32.3 Puppet Open Source Software
5.32.4 Puppet Orchestrator
5.32.5 Puppet Project Blueshift
5.33 QTS
5.33.1 QTS History
5.33.2 QTS Chicago Data Center
5.34 Qualcom
5.34.1 Qualcomm
5.34.2 Qualcomm Business
5.34.3 QMC Offers Comprehensive Chipset Solutions
5.34.4 Qualcomm Government Technologies
5.34.5 Qualcomm Internet Services
5.34.6 Qualcomm Ventures
5.34.7 Qualcomm Revenue
5.34.8 Qualcomm / WiPower
5.35 Rackspace
5.36 Red Hat / Ansible
5.37 Switch
5.37.1 Switch SUPERNAP CORE Cooperative: $3 Trillion Independent Purchasing And Collaboration Ecosystem
5.37.2 Switch SUPERNAP Edge
5.38 Tango
5.39 Tencent
5.40 Twitter
5.40.1 Twitter Revenue
5.40.2 Twitter Creation And Sharing Ideas And Information
5.40.3 Bringing Tweets To People
5.41 Yahoo
5.41.1 Yahoo Revenue
5.41.2 Yahoo Mavens Revenue
5.41.3 Yahoo Tumblr
5.41.4 Yahoo Tumblr Sponsored Posts
5.41.5 Yahoo Tumblr Sponsored Day
5.41.6 Yahoo Tumblr Use Case
5.41.7 Yahoo Display Revenue
5.41.8 Yahoo Display Metrics
5.41.9 Yahoo / Microsoft
5.41.10 Yahoo / Google
5.41.11 Yahoo / Tumblr
*If Applicable.
Links
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