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The Big Data Market: Business Case, Market Analysis & Forecasts 2016 - 2021

  • November 2016
  • -
  • Mind Commerce Publishing
  • -
  • 186 pages

Overview:

The management of unstructured data (e.g. Big Data), the leveraging of analytics tools to derive value, and the integration between Cloud, Internet of Things (IoT), and enterprise operational technology are key focus areas for large companies across virtually every industry vertical. However, Big Data and Analytics tools are not limited to large companies as products and services are emerging that are democratizing data for smaller companies.

A new data economy is developing in which the data associated with corporate products and services becomes almost as value as the company offerings themselves. New models are emerging to reduce friction across the value chain including enhanced Big Data as a Service (BDaaS) offerings. BDaaS is anticipated to make cross-industry, cross-company, and even cross-competitor data exchange a reality that adds value across the ecosystem with minimized security and privacy concerns.

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 chain analysis, case studies and a quantitative assessment of the industry with forecasting from 2016 to 2021.

Topics covered in the report include:
Big Data Technology: A review of the underlying technologies that resolve big data complexities
Big Data Use Cases: A review of investments sectors and specific use cases for the Big Data market
The Big Data Value Chain: An analysis of the value chain of Big Data and the major players involved within it
The Business Case for Big Data: An assessment of the business case, growth drivers and barriers for Big Data
Big Data Vendor Assessment: An assessment of the vendor landscape of leading players within the Big Data market
Market Analysis and Forecasts: A global and regional assessment of the market size and forecasts for 2016 to 2021
All purchases of Mind Commerce reports includes time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.

Key Findings:
The global Big Data Market will reach $72B USD by 2021 with a CAGR of 20.8%
Western Europe will be a market leader with $20.9B USD by 2021 with CAGR of 22.2%
Business Intelligence Tools and Analytics Platforms will reach $15.8B USD globally by 2021
Professional Services remains the leading revenue area through 2021 with CAGR of 23.8%
Open development tools and communities are driving innovation in key areas such as Cloud and IoT


Report Benefits:
Detailed forecasts 2016 - 2021
Learn about Big Data technologies
Identify leading market segments
Identify key players and strategies
Identify opportunities in data analytics
Understand market drivers and barriers
Understand the business case for Big Data
Understand regulatory issues and initiatives


Companies in Report:
1010Data
Accenture
Actian Corporation
Amazon
Apache Software Foundation
APTEAN
Booz Allen Hamilton
Bosch Software innovations: Bosch IoT Suite
Capgemini
Cisco Systems
Cloudera
CRAY Inc.
Computer Science Corporation
DataDirect Network
Dell
Deloitte
EMC
Facebook
Fujitsu
General Electric
GoodData Corporation
Google
Guavus
HP
Hitachi Data Systems
Hortonworks
IBM
Informatica
Intel
Jasper (Cisco)
Juniper Networks
Marklogic
Microsoft
MongoDB
MU Sigma
Netapp
NTT Data
Open Text (Actuate Corporation)
Opera Solutions
Oracle
Pentaho
Qlik Tech
Quantum
Rackspace
Revolution Analytics
Salesforce
SAP
SAS Institute
Sisense
Software AG/Terracotta
Splunk
Sqrrl
Supermicro
Tableau Software
Tata Consultancy Services
Teradata
Think Big Analytics
TIBCO
Tidemark Systems
VMware (Part of EMC)
Wipro
Workday (Platfora)
Zettics


Target Audience:
Network service providers
Systems integration companies
Big Data and Analytics companies
Advertising and media companies
Enterprise across all industry verticals
Cloud and IoT product and service providers

Table Of Contents

The Big Data Market: Business Case, Market Analysis and Forecasts 2016 - 2021
1 Background of the Study
1.1 Introduction
1.2 Scope of the Report
1.3 Target Audience
1.4 Companies in Report
2 Executive Summary
3 Big Data Technology and Business Case
3.1 Defining Big Data
3.2 Key Characteristics of Big Data
3.2.1 Volume
3.2.2 Variety
3.2.3 Velocity
3.2.4 Variability
3.2.5 Complexity
3.3 Big Data Technology
3.3.1 Hadoop
3.3.1.1 Other Apache Projects
3.3.2 NoSQL
3.3.2.1 Hbase
3.3.2.2 Cassandra
3.3.2.3 Mongo DB
3.3.2.4 Riak
3.3.2.5 CouchDB
3.3.3 MPP Databases
3.3.4 Other Emerging Technologies
3.3.4.1 Storm
3.3.4.2 Drill
3.3.4.3 Dremel
3.3.4.4 SAP HANA
3.3.4.5 Gremlin and Giraph
3.4 New Paradigms and Techniques
3.4.1 Streaming Analytics
3.4.2 Cloud Technology
3.4.3 Google Search
3.4.4 Customize Analytical Tools
3.4.5 Internet Keywords
3.4.6 Gamification
3.5 Big Data Roadmap
3.6 Market Drivers
3.6.1 Data Volume and Variety
3.6.2 Increasing Adoption of Big Data by Enterprises and Telecom
3.6.3 Maturation of Big Data Software
3.6.4 Continued Investments in Big Data by Web Giants
3.6.5 Business Drivers
3.7 Market Barriers
3.7.1 Privacy and Security: The 'Big' Barrier
3.7.2 Workforce Re-skilling and Organizational Resistance
3.7.3 Lack of Clear Big Data Strategies
3.7.4 Technical Challenges: Scalability and Maintenance
3.7.5 Big Data Development Expertise
4 Key Investment Sectors for Big Data
4.1 Industrial Internet and Machine-to-Machine
4.1.1 Big Data in M2M
4.1.2 Vertical Opportunities
4.2 Retail and Hospitality
4.2.1 Improving Accuracy of Forecasts and Stock Management
4.2.2 Determining Buying Patterns
4.2.3 Hospitality Use Cases
4.2.4 Personalized Marketing
4.3 Media
4.3.1 Social Media
4.3.2 Social Gaming Analytics
4.3.3 Usage of Social Media Analytics by Other Verticals
4.3.4 Internet Keyword Search
4.4 Utilities
4.4.1 Analysis of Operational Data
4.4.2 Application Areas for the Future
4.5 Financial Services
4.5.1 Fraud Analysis, Mitigation and Risk Profiling
4.5.2 Merchant-Funded Reward Programs
4.5.3 Customer Segmentation
4.5.4 Customer Retention and Personalized Product Offering
4.5.5 Insurance Companies
4.6 Healthcare and Pharmaceutical
4.6.1 Drug Development
4.6.2 Medical Data Analytics
4.6.3 Case Study: Identifying Heartbeat Patterns
4.7 Telecommunications
4.7.1 Telco Analytics: Customer/Usage Profiling and Service Optimization
4.7.2 Big Data Analytic Tools
4.7.3 Speech Analytics
4.7.4 New Products and Services
4.8 Government and Homeland Security
4.8.1 Big Data Research
4.8.2 Statistical Analysis
4.8.3 Language Translation
4.8.4 Developing New Applications for the Public
4.8.5 Tracking Crime
4.8.6 Intelligence Gathering
4.8.7 Fraud Detection and Revenue Generation
4.9 Other Sectors
4.9.1 Aviation
4.9.2 Transportation and Logistics: Optimizing Fleet Usage
4.9.3 Sports: Real-Time Processing of Statistics
4.9.4 Education
4.9.5 Manufacturing
5 The Big Data Value Chain
5.1 How Fragmented is the Big Data Value Chain?
5.2 Data Acquisitioning and Provisioning
5.3 Data Warehousing and Business Intelligence
5.4 Analytics and Visualization
5.5 Actioning and Business Process Management
5.6 Data Governance
6 Big Data Analytics
6.1 What is Big Data Analytics?
6.2 The Importance of Big Data Analytics
6.3 Reactive vs. Proactive Analytics
6.4 Technology and Implementation Approaches
6.4.1 Grid Computing
6.4.2 In-Database processing
6.4.3 In-Memory Analytics
6.4.4 Data Mining
6.4.5 Predictive Analytics
6.4.6 Natural Language Processing
6.4.7 Text Analytics
6.4.8 Visual Analytics
6.4.9 Association Rule Learning
6.4.10 Classification Tree Analysis
6.4.11 Machine Learning
6.4.12 Neural Networks
6.4.13 Multilayer Perceptron
6.4.14 Radial Basis Functions
6.4.14.1 Support Vector Machines
6.4.14.2 Naïve Bayes
6.4.14.3 K-nearest Neighbors
6.4.15 Geospatial Predictive Modelling
6.4.16 Regression Analysis
6.4.17 Social Network Analysis
7 Standardization and Regulatory Initiatives
7.1 Cloud Standards Customer Council
7.2 National Institute of Standards and Technology
7.3 OASIS
7.4 Open Data Foundation
7.5 Open Data Center Alliance
7.6 Cloud Security Alliance
7.7 International Telecommunications Union
7.8 International Organization for Standardization
8 Global Markets and Forecasts for Big Data
8.1 Global Big Data Markets 2016 - 2021
8.2 Regional Markets for Big Data 2016 - 2021
8.3 Big Data Revenue by Product Segment 2016 - 2021
8.3.1 Investments in Database Management Systems
8.3.2 Investments in Big Data Integration Tools
8.3.3 Investments in Application Infrastructure and Middleware
8.3.4 Investments in Business Intelligence Tools and Analytics Platforms
8.3.5 Big Data Investments in Professional Services 2016 - 2021
9 Key Players in the Big Data Market
9.1 Vendor Assessment Matrix
9.2 1010Data
9.3 Accenture
9.4 Actian Corporation
9.5 Amazon
9.6 Apache Software Foundation
9.7 APTEAN
9.8 Booz Allen Hamilton
9.9 Bosch Software Innovations: Bosch IoT Suite
9.10 Capgemini
9.11 Cisco Systems
9.12 Cloudera
9.13 CRAY Inc.
9.14 Computer Science Corporation
9.15 DataDirect Network
9.16 Dell
9.17 Deloitte
9.18 EMC
9.19 Facebook
9.20 Fujitsu
9.21 General Electric
9.22 GoodData Corporation
9.23 Google
9.24 Guavus
9.25 HP
9.26 Hitachi Data Systems
9.27 Hortonworks
9.28 IBM
9.29 Informatica
9.30 Intel
9.31 Jasper (Cisco)
9.32 Juniper Networks
9.33 Marklogic
9.34 Microsoft
9.35 MongoDB
9.36 MU Sigma
9.37 Netapp
9.38 NTT Data
9.39 Open Text (Actuate Corporation)
9.40 Opera Solutions
9.41 Oracle
9.42 Pentaho
9.43 Qlik Tech
9.44 Quantum
9.45 Rackspace
9.46 Revolution Analytics
9.47 Salesforce
9.48 SAP
9.49 SAS Institute
9.50 Sisense
9.51 Software AG/Terracotta
9.52 Splunk
9.53 Sqrrl
9.54 Supermicro
9.55 Tableau Software
9.56 Tata Consultancy Services
9.57 Teradata
9.58 Think Big Analytics
9.59 TIBCO
9.60 Tidemark Systems
9.61 VMware (EMC)
9.62 Wipro
9.63 Workday (Platfora)
9.64 Zettics

Figures

Figure 1: Key Characteristics of Big Data
Figure 2: NoSQL vs Legacy DB Performance Comparisons
Figure 3: Roadmap Big Data Technologies 2016 - 2030
Figure 4: The Big Data Value Chain
Figure 5: Big Data Value Flow
Figure 6: Big Data Analytics
Figure 7: Global Big Data Markets 2016 - 2021
Figure 8: Regional Big Data Markets 2016 - 2021
Figure 9: Investments in Database Management Systems 2016 - 2021
Figure 10: Investments in Data Integration and Quality Tools 2016 - 2021
Figure 11: Investments in Application Infrastructure and Middleware 2016 - 2021
Figure 12: Investments in Business Intelligence Tools and Analytics Platforms 2016 - 2021
Figure 13: Big Data Investments in Professional Services 2016 - 2021
Figure 14: Big Data Vendor Ranking Matrix

Tables

Table 1: Global Big Data Markets 2016 - 2021
Table 2: Regional Big Data Markets 2016 - 2021
Table 3: Big Data Markets by Product Segments 2016 - 2021
Table 4: Investments in Database Management Systems 2016 - 2021
Table 5: Investments in Data Integration Tools 2016 - 2021
Table 6: Investments in Application Infrastructure and Middleware 2016 - 2021
Table 7: Investments in Business Intelligence Tools and Analytics Platforms 2016 - 2021
Table 8: Big Data Investments in Professional Services 2016 - 2021
Table 9: Big Data Analytics Platforms by Company

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