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The Big Data Market: Business Case, Market Analysis & Forecasts 2015 - 2020 - Product Image

The Big Data Market: Business Case, Market Analysis & Forecasts 2015 - 2020

  • ID: 2983902
  • September 2014
  • Region: Global
  • 141 Pages
  • Mind Commerce LLC
It is estimated that global spending on Big Data will grow at a CAGR of 46% between 2015 and 2020. Big Data revenues will reach almost $190 Billion by the end of 2020

FEATURED COMPANIES

  • 1010Data
  • Cisco Systems
  • Harley Davidson
  • Microsoft
  • Quantum
  • Splunk
  • MORE

Big Data refers to a massive volume of both structured and unstructured data that is so large that it is difficult to process using traditional database and software techniques. While the presence of such datasets is not something new, the past few years have witnessed immense commercial investments in solutions that address the processing and analysis of Big Data. Big Data opens a vast array of applications and opportunities in multiple vertical sectors including, but not limited to, retail and hospitality, media, utilities, financial services, healthcare and pharmaceutical, telecommunications, government, homeland security, and the emerging industrial Internet vertical.

Despite challenges, such as the lack of clear big data strategies, security concerns and the need for workforce re-skilling, the growth potential of Big Data is unprecedented. It is estimated that global spending on Big Data will grow at a CAGR of 46% between 2015 and 2020. Big Data revenues will reach almost $190 Billion by the end of 2020.

This report provides an in-depth assessment of the global Big Data market, including a study of the business case, application use cases, vendor landscape, value READ MORE >

Note: Product cover images may vary from those shown
It is estimated that global spending on Big Data will grow at a CAGR of 46% between 2015 and 2020. Big Data revenues will reach almost $190 Billion by the end of 2020

FEATURED COMPANIES

  • 1010Data
  • Cisco Systems
  • Harley Davidson
  • Microsoft
  • Quantum
  • Splunk
  • MORE

1 Introduction
1.1 Executive Summary
1.2 Topics Covered
1.3 Key Findings
1.4 Target Audience
1.5 Companies Mentioned

2 Big Data Technology & Business Case
2.1 Defining Big Data
2.2 Key Characteristics of Big Data
2.2.1 Volume
2.2.2 Variety
2.2.3 Velocity
2.2.4 Variability
2.2.5 Complexity
2.3 Big Data Technology
2.3.1 Hadoop
2.3.2 Other Apache Projects
2.3.3 NoSQL
2.3.3.1 Hbase
2.3.3.2 Cassandra
2.3.3.3 Mongo DB
2.3.3.4 Riak
2.3.3.5 CouchDB
2.3.4 MPP Databases
2.3.5 Others and Emerging Technologies
2.3.5.1 Storm
2.3.5.2 Drill
2.3.5.3 Dremel
2.3.5.4 SAP HANA
2.3.5.5 Gremlin & Giraph
2.3.6 New Paradigms and Techniques
2.3.6.1 Streaming Analytics
2.3.6.2 Cloud Technology
2.3.6.3 Google Search
2.3.6.4 Customize Analytical Tools
2.3.6.5 Internet Keywords
2.3.6.6 Gamification
2.4 Big Data Roadmap
2.5 Market Drivers
2.5.1 Data Volume & Variety
2.5.2 Increasing Adoption of Big Data by Enterprises and Telecom
2.5.3 Maturation of Big Data Software
2.5.4 Continued Investments in Big Data by Web Giants
2.5.5 Business Drivers
2.6 Market Barriers
2.6.1 Privacy and Security: The ‘Big’ Barrier
2.6.2 Workforce Re-skilling and Organizational Resistance
2.6.3 Lack of Clear Big Data Strategies
2.6.4 Technical Challenges: Scalability & Maintenance
2.6.5 Big Data Development Expertise

3 Key Investment Sectors for Big Data
3.1 Industrial Internet and Machine-to-Machine
3.1.1 Big Data in M2M
3.1.2 Vertical Opportunities
3.2 Retail and Hospitality
3.2.1 Improving Accuracy of Forecasts & Stock Management
3.2.2 Determining Buying Patterns
3.2.3 Hospitality Use Cases
3.2.4 Personalized Marketing
3.3 Media
3.3.1 Social Media
3.3.2 Social Gaming Analytics
3.3.3 Usage of Social Media Analytics by Other Verticals
3.3.4 Internet Keyword Search
3.4 Utilities
3.4.1 Analysis of Operational Data
3.4.2 Application Areas for the Future
3.5 Financial Services
3.5.1 Fraud Analysis, Mitigation & Risk Profiling
3.5.2 Merchant-Funded Reward Programs
3.5.3 Customer Segmentation
3.5.4 Customer Retention & Personalized Product Offering
3.5.5 Insurance Companies
3.6 Healthcare and Pharmaceutical
3.6.1 Drug Development
3.6.2 Medical Data Analytics
3.6.3 Case Study: Identifying Heartbeat Patterns
3.7 Telecommunications
3.7.1 Telco Analytics: Customer/Usage Profiling and Service Optimization
3.7.2 Big Data Analytic Tools
3.7.3 Speech Analytics
3.7.4 New Products and Services
3.8 Government and Homeland Security
3.8.1 Big Data Research
3.8.2 Statistical Analysis
3.8.3 Language Translation
3.8.4 Developing New Applications for the Public
3.8.5 Tracking Crime
3.8.6 Intelligence Gathering
3.8.7 Fraud Detection & Revenue Generation
3.9 Other Sectors
3.9.1 Aviation
3.9.2 Transportation & Logistics: Optimizing Fleet Usage
3.9.3 Sports: Real-Time Processing of Statistics
3.9.4 Education
3.9.5 Manufacturing

4 The Big Data Value Chain
4.1 How Fragmented is the Big Data Value Chain?
4.2 Data Acquisitioning & Provisioning
4.3 Data Warehousing & Business Intelligence
4.4 Analytics & Virtualization
4.5 Actioning and Business Process Management
4.6 Data Governance

5 Big Data Analytics
5.1 What is Big Data Analytics?
5.2 The Importance of Big Data Analytics
5.3 Reactive vs. Proactive Analytics
5.4 Technology and Implementation Approaches
5.4.1 Grid Computing
5.4.2 In-Database processing
5.4.3 In-Memory Analytics
5.4.4 Data Mining
5.4.5 Predictive Analytics
5.4.6 Natural Language Processing
5.4.7 Text Analytics
5.4.8 Visual Analytics
5.4.9 Association rule learning
5.4.10 Classification tree analysis
5.4.11 Machine Learning
5.4.11.1 Neural networks
5.4.11.2 Multilayer Perceptron (MLP)
5.4.11.3 Radial Basis Functions
5.4.11.4 Support vector machines
5.4.11.5 Naïve Bayes
5.4.11.6 k-nearest neighbors
5.4.11.7 Geospatial predictive modelling
5.4.12 Regression Analysis
5.4.13 Social Network Analysis

6 Standardization and Regulatory Initiatives
6.1 Cloud Standards Customer Council – Big Data Working Group
6.2 National Institute of Standards and Technology – Big Data Working Group
6.3 OASIS
6.4 Open Data Foundation
6.5 Open Data Center Alliance
6.6 Cloud Security Alliance – Big Data Working Group
6.7 International Telecommunications Union
6.8 International Organization for Standardization
6.9 International Organization for Standardization)

7 Key Players in the Big Data Market
7.1 Vendor Assessment Matrix
7.2 1010Data
7.3 Actuate Corporation
7.4 Accenture
7.5 Amazon
7.6 Apache Software Foundation
7.7 APTEAN (Formerly CDC Software)
7.8 Booz Allen Hamilton
7.9 Cap Gemini
7.10 Cisco Systems
7.11 Cloudera
7.12 Computer Science Corporation
7.13 DataDirect Network
7.14 Dell
7.15 Deloitte
7.16 EMC
7.17 Facebook
7.18 Fujitsu
7.19 General Electric
7.20 GoodData Corporation
7.21 Google
7.22 Guavus
7.23 Hitachi Data Systems
7.24 Hortonworks
7.25 HP
7.26 IBM
7.27 Informatica
7.28 Intel
7.29 Jaspersoft
7.30 Juniper Networks
7.31 Marklogic
7.32 Microsoft
7.33 MongoDB (Formerly 10Gen)
7.34 MU Sigma
7.35 Netapp
7.36 NTT Data
7.37 Opera Solutions
7.38 Oracle
7.39 Pentaho
7.40 Platfora
7.41 Qliktech
7.42 Quantum
7.43 Rackspace
7.44 Revolution Analytics
7.45 Salesforce
7.46 SAP
7.47 SAS Institute
7.48 Sisense
7.49 Software AG/Terracotta
7.50 Splunk
7.51 Sqrrl
7.52 Supermicro
7.53 Tableau Software
7.54 Tata Consultancy Services
7.55 Teradata
7.56 Think Big Analytics
7.57 TIBCO
7.58 Tidemark Systems
7.59 VMware (Part of EMC)
7.60 Wipro
7.61 Zettics

8 Market Analysis
8.1 Big Data Revenue 2014 - 2020
8.2 Big Data Revenue by Functional Area 2014 - 2020
8.2.1 Supply Chain Management
8.2.2 Business Intelligence
8.2.3 Application Infrastructure & Middleware
8.2.4 Data Integration Tools & Data Quality Tools
8.2.5 Database Management Systems
8.2.6 Big Data Social & Content Analytics
8.2.7 Big Data Storage Management
8.2.8 Big Data Professional Services
8.3 Big Data Revenue by Region 2014 - 2020
8.3.1 Asia Pacific
8.3.2 Eastern Europe
8.3.3 Latin & Central America
8.3.4 Middle East & Africa
8.3.5 North America
8.3.6 Western Europe

List of Figures:

Figure 1: NoSQL vs Legacy DB Performance Comparisons
Figure 2: 2014 Gartner Hype Cycle for Emerging Technologies
Figure 3: Roadmap Big Data Technologies 2014 - 2030
Figure 4: The Big Data Value Chain
Figure 5: Big Data Vendor Ranking Matrix
Figure 6: Big Data Revenue 2013 – 2020
Figure 7: Big Data Revenue by Functional Area 2013 – 2020
Figure 8: Big Data Supply Chain Management Revenue 2013 – 2020
Figure 9: Big Data Supply Business Intelligence Revenue 2013 – 2020
Figure 10: Big Data Application Infrastructure & Middleware Revenue 2013 – 2020
Figure 11: Big Data Integration and Quality Tools Revenue 2013 – 2020
Figure 12: Big Data DB Management Systems Revenue 2013 – 2020
Figure 13: Big Data Social & Content Analytics Revenue 2013 – 2020
Figure 14: Big Data Storage Management Revenue 2013 – 2020
Figure 15: Big Data Professional Services Revenue 2013 – 2020
Figure 16: Big Data Revenue by Region 2013 – 2020
Figure 17: Asia Pacific Big Data Revenue 2013 – 2020
Figure 18: Eastern Europe Big Data Revenue 2013 – 2020
Figure 19: Latin & Central America Big Data Revenue 2013 – 2020
Figure 20: Middle East & Africa Big Data Revenue 2013 – 2020
Figure 21: North America Big Data Revenue 2013 – 2020
Figure 22: Western Europe Big Data Revenue 2013 – 2020

Note: Product cover images may vary from those shown
It is estimated that global spending on Big Data will grow at a CAGR of 46% between 2015 and 2020. Big Data revenues will reach almost $190 Billion by the end of 2020

- 1010Data
- APTEAN (Formerly CDC Software)
- Accenture
- Actuate Corporation
- Adaptive
- Adobe
- Amazon
- Apache Software Foundation
- Bank of America
- Bill & Melinda Gates Foundation
- Booz Allen Hamilton
- Bristol Myers Squibb
- Brooks Brothers
- CIA
- CapGemini
- Carnegie Corporation
- Centre for Economics and Business Research
- Cisco Systems
- Cloud Security Alliance (CSA)
- Cloud Standard Customer Council
- Cloudera
- Computer Science Corporation
- DARPA
- Data Direct Network
- Deliotte
- Dell
- EMC
- Facebook
- Fujitsu
- General Electric
- GoodData Corporation
- Google
- Guavus
- HP
- Harley Davidson
- Hitachi Data Systems
- Hortonworks
- IBM
- inBloom
- Informatica
- Intel
- International Standards Organization (ISO)
- International Telecommunications Union (ITU)
- JP Morgan Chase
- Jaspersoft
- Juniper Networks
- MU Sigma
- MarkLogic
- McLaren Racing Team
- Microsoft
- MongoDB (Formerly 10Gen)
- Morgan Stanley
- NSA
- National Institute of Standards & Technology (NIST)
- Netapp
- New Classrooms Innovation Partners
- OASIS
- Open Data Center Alliance
- Open Data Foundation (ODaF)
- Opera Solutions
- Oracle
- Pentaho
- Platfora
- Qliktech
- Quantum
- Rackspace
- Raytheon
- Renaissance Learning
- Revolution Analytics
- Rockwell Automation
- SAP
- SAS Institute
- Salesforce
- Sherwin Williams
- Siemans
- Sisense
- Software AG/Terracotta
- Splunk
- Sqrrl
- Supermicro
- T-Mobile
- TIBCO
- Tableau Software
- Tata Consultancy Services
- Teradata
- Think Big Analytics
- Tidemark Systems
- TomTom
- Twitter
- US Federal Government (various agencies and departments)
- US Xpress
- VMware (Part of EMC)
- Vodafone
- Wipro
- Zettics

Note: Product cover images may vary from those shown
Note: Product cover images may vary from those shown

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