【レポートの概要（一部）】
1 Chapter 1: Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Historical Revenue & Forecast Segmentation
1.4 Key Questions Answered
1.5 Key Findings
1.6 Methodology
1.7 Target Audience
1.8 Companies & Organizations Mentioned
2 Chapter 2: An Overview of Big Data
2.1 What is Big Data?
2.2 Key Approaches to Big Data Processing
2.2.1 Hadoop
2.2.2 NoSQL
2.2.3 MPAD (Massively Parallel Analytic Databases)
2.2.4 In-memory Processing
2.2.5 Stream Processing Technologies
2.2.6 Spark
2.2.7 Other Databases & Analytic Technologies
2.3 Key Characteristics of Big Data
2.3.1 Volume
2.3.2 Velocity
2.3.3 Variety
2.3.4 Value
2.4 Market Growth Drivers
2.4.1 Awareness of Benefits
2.4.2 Maturation of Big Data Platforms
2.4.3 Continued Investments by Web Giants, Governments & Enterprises
2.4.4 Growth of Data Volume, Velocity & Variety
2.4.5 Vendor Commitments & Partnerships
2.4.6 Technology Trends Lowering Entry Barriers
2.5 Market Barriers
2.5.1 Lack of Analytic Specialists
2.5.2 Uncertain Big Data Strategies
2.5.3 Organizational Resistance to Big Data Adoption
2.5.4 Technical Challenges: Scalability & Maintenance
2.5.5 Security & Privacy Concerns
3 Chapter 3: Vertical Opportunities & Use Cases for Big Data
3.1 Automotive, Aerospace & Transportation
3.1.1 Predictive Warranty Analysis
3.1.2 Predictive Aircraft Maintenance & Fuel Optimization
3.1.3 Air Traffic Control
3.1.4 Transport Fleet Optimization
3.2 Banking & Securities
3.2.1 Customer Retention & Personalized Product Offering
3.2.2 Risk Management
3.2.3 Fraud Detection
3.2.4 Credit Scoring
3.3 Defense & Intelligence
3.3.1 Intelligence Gathering
3.3.2 Energy Saving Opportunities in the Battlefield
3.3.3 Preventing Injuries on the Battlefield
3.4 Education
3.4.1 Information Integration
3.4.2 Identifying Learning Patterns
3.4.3 Enabling Student-Directed Learning
3.5 Healthcare & Pharmaceutical
3.5.1 Managing Population Health Efficiently
3.5.2 Improving Patient Care with Medical Data Analytics
3.5.3 Improving Clinical Development & Trials
3.5.4 Improving Time to Market
3.6 Smart Cities & Intelligent Buildings
3.6.1 Energy Optimization & Fault Detection
3.6.2 Intelligent Building Analytics
3.6.3 Urban Transportation Management
3.6.4 Optimizing Energy Production
3.6.5 Water Management
3.6.6 Urban Waste Management
3.7 Insurance
3.7.1 Claims Fraud Mitigation
3.7.2 Customer Retention & Profiling
3.7.3 Risk Management
3.8 Manufacturing & Natural Resources
3.8.1 Asset Maintenance & Downtime Reduction
3.8.2 Quality & Environmental Impact Control
3.8.3 Optimized Supply Chain
3.8.4 Exploration & Identification of Wells & Mines
3.8.5 Maximizing the Potential of Drilling
3.8.6 Production Optimization
3.9 Web, Media & Entertainment
3.9.1 Audience & Advertising Optimization
3.9.2 Channel Optimization
3.9.3 Recommendation Engines
3.9.4 Optimized Search
3.9.5 Live Sports Event Analytics
3.9.6 Outsourcing Big Data Analytics to Other Verticals
3.10 Public Safety & Homeland Security
3.10.1 Cyber Crime Mitigation
3.10.2 Crime Prediction Analytics
3.10.3 Video Analytics & Situational Awareness
3.11 Public Services
3.11.1 Public Sentiment Analysis
3.11.2 Fraud Detection & Prevention
3.11.3 Economic Analysis
3.12 Retail & Hospitality
3.12.1 Customer Sentiment Analysis
3.12.2 Customer & Branch Segmentation
3.12.3 Price Optimization
3.12.4 Personalized Marketing
3.12.5 Optimized Supply Chain
3.13 Telecommunications
3.13.1 Network Performance & Coverage Optimization
3.13.2 Customer Churn Prevention
3.13.3 Personalized Marketing
3.13.4 Location Based Services
3.13.5 Fraud Detection
3.14 Utilities & Energy
3.14.1 Customer Retention
3.14.2 Forecasting Energy
3.14.3 Billing Analytics
3.14.4 Predictive Maintenance
3.14.5 Turbine Placement Optimization
3.15 Wholesale Trade
3.15.1 In-field Sales Analytics
3.15.2 Monitoring the Supply Chain
4 Chapter 4: Big Data Industry Roadmap & Value Chain
4.1 Big Data Industry Roadmap
4.1.1 2010 – 2013: Initial Hype and the Rise of Analytics
4.1.2 2014 – 2017: Emergence of SaaS Based Big Data Solutions
4.1.3 2018 – 2020: Growing Adoption of Scalable Machine Learning
4.1.4 2021 & Beyond: Widespread Investments on Cognitive & Personalized Analytics
4.2 The Big Data Value Chain
4.2.1 Hardware Providers
4.2.1.1 Storage & Compute Infrastructure Providers
4.2.1.2 Networking Infrastructure Providers
4.2.2 Software Providers
4.2.2.1 Hadoop & Infrastructure Software Providers
4.2.2.2 SQL & NoSQL Providers
4.2.2.3 Analytic Platform & Application Software Providers
4.2.2.4 Cloud Platform Providers
4.2.3 Professional Services Providers
4.2.4 End-to-End Solution Providers
4.2.5 Vertical Enterprises
5 Chapter 5: Big Data Analytics
5.1 What are Big Data Analytics?
5.2 The Importance of Analytics
5.3 Reactive vs. Proactive Analytics
5.4 Customer vs. Operational Analytics
5.5 Technology & Implementation Approaches
5.5.1 Grid Computing
5.5.2 In-Database Processing
5.5.3 In-Memory Analytics
5.5.4 Machine Learning & Data Mining
5.5.5 Predictive Analytics
5.5.6 NLP (Natural Language Processing)
5.5.7 Text Analytics
5.5.8 Visual Analytics
5.5.9 Social Media, IT & Telco Network Analytics
5.6 Vertical Market Case Studies
5.6.1 Amazon – Delivering Cloud Based Big Data Analytics
5.6.2 Facebook – Using Analytics to Monetize Users with Advertising
5.6.3 WIND Mobile – Using Analytics to Monitor Video Quality
5.6.4 Coriant Analytics Services – SaaS Based Big Data Analytics for Telcos
5.6.5 Boeing – Analytics for the Battlefield
5.6.6 The Walt Disney Company – Utilizing Big Data and Analytics in Theme Parks
6 Chapter 6: Standardization & Regulatory Initiatives
6.1 CSCC (Cloud Standards Customer Council) – Big Data Working Group
6.2 NIST (National Institute of Standards and Technology) – Big Data Working Group
6.3 OASIS –Technical Committees
6.4 ODaF (Open Data Foundation)
6.5 Open Data Center Alliance
6.6 CSA (Cloud Security Alliance) – Big Data Working Group
6.7 ITU (International Telecommunications Union)
6.8 ISO (International Organization for Standardization) and Others
7 Chapter 7: Market Analysis & Forecasts
7.1 Global Outlook of the Big Data Market
7.2 Submarket Segmentation
7.2.1 Storage and Compute Infrastructure
7.2.2 Networking Infrastructure
7.2.3 Hadoop & Infrastructure Software
7.2.4 SQL
7.2.5 NoSQL
7.2.6 Analytic Platforms & Applications
7.2.7 Cloud Platforms
7.2.8 Professional Services
7.3 Vertical Market Segmentation
7.3.1 Automotive, Aerospace & Transportation
7.3.2 Banking & Securities
7.3.3 Defense & Intelligence
7.3.4 Education
7.3.5 Healthcare & Pharmaceutical
7.3.6 Smart Cities & Intelligent Buildings
7.3.7 Insurance
7.3.8 Manufacturing & Natural Resources
7.3.9 Media & Entertainment
7.3.10 Public Safety & Homeland Security
7.3.11 Public Services
7.3.12 Retail & Hospitality
7.3.13 Telecommunications
7.3.14 Utilities & Energy
7.3.15 Wholesale Trade
7.3.16 Other Sectors
7.4 Regional Outlook
7.5 Asia Pacific
7.5.1 Country Level Segmentation
7.5.2 Australia
7.5.3 China
7.5.4 India
7.5.5 Indonesia
7.5.6 Japan
7.5.7 Malaysia
7.5.8 Pakistan
7.5.9 Philippines
7.5.10 Singapore
7.5.11 South Korea
7.5.12 Taiwan
7.5.13 Thailand
7.5.14 Rest of Asia Pacific
7.6 Eastern Europe
7.6.1 Country Level Segmentation
7.6.2 Czech Republic
7.6.3 Poland
7.6.4 Russia
7.6.5 Rest of Eastern Europe
7.7 Latin & Central America
7.7.1 Country Level Segmentation
7.7.2 Argentina
7.7.3 Brazil
7.7.4 Mexico
7.7.5 Rest of Latin & Central America
7.8 Middle East & Africa
7.8.1 Country Level Segmentation
7.8.2 Israel
7.8.3 Qatar
7.8.4 Saudi Arabia
7.8.5 South Africa
7.8.6 UAE
7.8.7 Rest of the Middle East & Africa
7.9 North America
7.9.1 Country Level Segmentation
7.9.2 Canada
7.9.3 USA
7.10 Western Europe
7.10.1 Country Level Segmentation
7.10.2 Denmark
7.10.3 Finland
7.10.4 France
7.10.5 Germany
7.10.6 Italy
7.10.7 Netherlands
7.10.8 Norway
7.10.9 Spain
7.10.10 Sweden
7.10.11 UK
7.10.12 Rest of Western Europe
8 Chapter 8: Vendor Landscape
8.1 1010data
8.2 Accenture
8.3 Actian Corporation
8.4 Actuate Corporation
8.5 Adaptive Insights
8.6 Advizor Solutions
8.7 AeroSpike
8.8 AFS Technologies
8.9 Alpine Data Labs
8.10 Alteryx
8.11 Altiscale
8.12 Antivia
8.13 Arcplan
8.14 Attivio
8.15 Automated Insights
8.16 AWS (Amazon Web Services)
8.17 Ayasdi
8.18 Basho
8.19 BeyondCore
8.20 Birst
8.21 Bitam
8.22 Board International
8.23 Booz Allen Hamilton
8.24 Capgemini
8.25 Cellwize
8.26 Centrifuge Systems
8.27 CenturyLink
8.28 Chartio
8.29 Cisco Systems
8.30 ClearStory Data
8.31 Cloudera
8.32 Comptel
8.33 Concurrent
8.34 Contexti
8.35 Couchbase
8.36 CSC (Computer Science Corporation)
8.37 DataHero
8.38 Datameer
8.39 DataRPM
8.40 DataStax
8.41 Datawatch Corporation
8.42 DDN (DataDirect Network)
8.43 Decisyon
8.44 Dell
8.45 Deloitte
8.46 Denodo Technologies
8.47 Digital Reasoning
8.48 Dimensional Insight
8.49 Domo
8.50 Dundas Data Visualization
8.51 Eligotech
8.52 EMC Corporation
8.53 Engineering Group (Engineering Ingegneria Informatica)
8.54 eQ Technologic
8.55 Facebook
8.56 FICO
8.57 Fractal Analytics
8.58 Fujitsu
8.59 Fusion-io
8.60 GE (General Electric)
8.61 GoodData Corporation
8.62 Google
8.63 Guavus
8.64 HDS (Hitachi Data Systems)
8.65 Hortonworks
8.66 HP
8.67 IBM
8.68 iDashboards
8.69 Incorta
8.70 InetSoft Technology Corporation
8.71 InfiniDB
8.72 Infor
8.73 Informatica Corporation
8.74 Information Builders
8.75 Intel
8.76 Jedox
8.77 Jinfonet Software
8.78 Juniper Networks
8.79 Knime
8.80 Kofax
8.81 Kognitio
8.82 L-3 Communications
8.83 Lavastorm Analytics
8.84 Logi Analytics
8.85 Looker Data Sciences
8.86 LucidWorks
8.87 Manthan Software Services
8.88 MapR
8.89 MarkLogic
8.90 MemSQL
8.91 Microsoft
8.92 MicroStrategy
8.93 MongoDB (formerly 10gen)
8.94 Mu Sigma
8.95 NTT Data
8.96 Neo Technology
8.97 NetApp
8.98 OpenText Corporation
8.99 Opera Solutions
8.100 Oracle
8.101 Palantir Technologies
8.102 Panorama Software
8.103 ParStream
8.104 Pentaho
8.105 Phocas
8.106 Pivotal Software
8.107 Platfora
8.108 Prognoz
8.109 PwC
8.110 Pyramid Analytics
8.111 Qlik
8.112 Quantum Corporation
8.113 Qubole
8.114 Rackspace
8.115 RainStor
8.116 RapidMiner
8.117 Recorded Future
8.118 Revolution Analytics
8.119 RJMetrics
8.120 Salesforce.com
8.121 Sailthru
8.122 Salient Management Company
8.123 SAP
8.124 SAS Institute
8.125 SGI
8.126 SiSense
8.127 Software AG
8.128 Splice Machine
8.129 Splunk
8.130 Sqrrl
8.131 Strategy Companion
8.132 Supermicro
8.133 SynerScope
8.134 Tableau Software
8.135 Talend
8.136 Targit
8.137 TCS (Tata Consultancy Services)
8.138 Teradata
8.139 Think Big Analytics
8.140 ThoughtSpot
8.141 TIBCO Software
8.142 Tidemark
8.143 VMware (EMC Subsidiary)
8.144 WiPro
8.145 Yellowfin International
8.146 Zettics
8.147 Zoomdata
8.148 Zucchetti
9 Chapter 9: Conclusion & Strategic Recommendations
9.1 Big Data Technology: Beyond Data Capture & Analytics
9.2 Transforming IT from a Cost Center to a Profit Center
9.3 Can Privacy Implications Hinder Success?
9.4 Will Regulation have a Negative Impact on Big Data Investments?
9.5 Battling Organization & Data Silos
9.6 Software vs. Hardware Investments
9.7 Vendor Share: Who Leads the Market?
9.8 Big Data Driving Wider IT Industry Investments
9.9 Assessing the Impact of IoT & M2M
9.10 Recommendations
9.10.1 Big Data Hardware, Software & Professional Services Providers
9.10.2 Enterprises
【レポート販売概要】
■ タイトル：世界のビックデータ市場：機会、課題、戦略、産業、予測■ 英文：The Big Data Market: 2015 – 2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts
■ 発行日：2015年5月25日
■ 調査会社：Signals and Systems Telecom
■ 商品コード：SNST50602
■ 調査対象地域：グローバル
- 食品/飲料包装用金属缶の世界市場2015-2019About metal cans Packaging in broad terms means the technology of enclosing a product for storage, distribution, sale, and use. Metal can packaging is one of the types of packaging. A metal can is a container for the storage and distribution of goods, and is composed of thin metal, usually steel or aluminum. These metal cans hold a wide range of products such as food, beverages, oils, and chemical …
- 整形外科向けソフトウェアの世界市場：術前計画ソフトウェア、電子カルテ、PACSOrthopedic software is used before, during and after orthopedic surgeries by surgeons. While there are different types of software used by orthopedic surgeons, digital templating software is most widely used, as they enable advanced orthopedic surgical planning. Orthopedic EHR and orthopedic picture archiving and communication systems (PACS) are also some of the other software preferred by orthope …
- 電線の世界市場：低圧電線、中圧電線、高圧電線About Power Cables A power cable is an insulated strand of wires bundled together to convey electricity at different voltage levels. Power cables are mainly used in overhead lines and underground cabling applications. These can be classified into three broad categories depending on their operating voltage applications: LV, MV, and HV. Technavio’s analysts forecast the global power cables market to …
- 世界の神経修復・神経再生市場：異種移植片、神経調節、手術などThe nerve repair and regeneration market was worth $4.1 billion in 2012 and is expected to grow at a CAGR of 11.5% in the next five years, primarily due to technological advancements and favorable reimbursement policies. The market is expected to witness a high growth in nerve grafting and neuromodulation segments, as they offer effective solutions for peripheral nerve repair and chronic pain, inc …
- 世界のシンチレータ市場予測と分析：無機シンチレータ、有機シンチレータScintillators are luminescent materials, which re-emit part of the absorbed energy in the form of light. The emission can be of different types: fluorescence (prompt), delayed fluorescence and phosphorescence (delayed with different wavelength). The radiation detection and monitoring has witnessed various technological advancements in recent years. This advancement has led to the rise in the marke …
- 神経血管インターベンション（Neurovascular Intervention）：企業動向MediPoint: Neurovascular Interventions - Current and Future Players Summary The global neurovascular interventions market is a vast, double-digit market that consists of innovative and emerging technologies. Rapid advances in the field of neurovascular interventions and development of minimally invasive techniques have greatly expanded the potential of therapeutic applications. The neurovascular i …
- フットボールアパレルの世界市場2016-2020About Football Apparel Football apparel includes shirts, shorts and pants, socks, jackets, sweatshirts, rainwear, tracksuits, training bibs, T-shirts, and sleeves. The global football apparel market accounts for the largest share of the global ball sports apparel market. This will likely to continue over the forecast period, owing to the prevailing popularity of football. Europe is the major contr …
- スマートシティの世界市場：展望及び予測A large percentage of the global population lives in an urban environment, a rapidly accelerating trend that is taxing the resources and management capabilities of city governments. In addition, the enhanced mobility of modern society has created extreme competition between cities to attract skilled residents, corporations, and jobs. Smart Cities are much more than just an effort by sovereign nati …
- 自動車産業におけるセンサーの市場機会Under the trend where everything is connected to the Internet, the cost share of automotive applications in the electronic industry is also rising fast. This is attributed mainly to increasing needs for safer, more environmentally friendly and comfortable applications on telematics platforms. Active and passive safety systems like ADAS (Advanced Driver Assistance System) have recently been the are …
- モバイル・ラーニング・ソリューションの世界市場In today’s digital age, the use of technology can be seen in nearly every sector of the market. Education and training domain also has been impacted by it. The latest development is the mobile learning solutions which enable companies and educational institutions to provide training and learning through mobile devices and smartphones. The mobile learning market has gained significant traction in t …
- 世界の電子産業における3Dプリンティング市場2015-2019About 3D printing in electronics industry 3D printing, also known as AM, is the process of making a 3D model by laying down many successive layers of a 3D material. It helps in manufacturing customized products at a mass level without incurring extra costs and other environmental impacts. During the advent of this technology, these models were restricted to prototyping purposes, but in recent time …
- 世界のシェールガス処理装置市場動向と予測（～2019）This report estimates the shale gas processing equipment market, in terms of value. The value of this market is estimated in terms of $million and this has been broken down into geographical regions, and further split into processing components. Shale gas processing equipment are required for processing shale gas before it can be transported by large diameter inter-state or intra-state pipelines f …
- ドイツの血液検査市場2014This report provides an overview of the German hematology market, including sales and market shares of leading instrument and consumable suppliers, as well as test volume and sales forecasts by market segment.Table of ContentsBusiness EnvironmentMarket Structure Market Size, Growth, and Major Suppliers' Market Shares &n …
- 中小企業向けクラウドサービスの世界市場：パブリッククラウド、プライベートクラウド、ハイブリッドクラウドAbout SME Cloud The adoption of cloud-based services is increasing worldwide. Many large enterprises are already experiencing the benefits of using cloud-based technology for their business operations. The scenario is shifting toward SMEs because they can avoid investment on IT infrastructure and reduce operational costs by adopting cloud-based technology for their daily business operations. Cloud …
- 油圧シリンダーの世界市場2016-2020：農業、建設業、鉱業、資材運搬機器産業、産業機器産業、航空宇宙・防衛産業About Hydraulic Cylinder The hydraulic cylinder industry will see a steady growth during the forecast period due to a continuous demand from the agriculture, construction equipment, mining equipment, material handling equipment, industrial equipment, aerospace, and defense sectors. Technavio’s analysts forecast the global hydraulic cylinder market to grow at a CAGR of 4.39% during the period 2016- …
