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Big Data Market: Business Case, Market Analysis and Forecasts 2014 - 2019 - Product Image

Big Data Market: Business Case, Market Analysis and Forecasts 2014 - 2019

  • Published: September 2013
  • 66 Pages
  • Mind Commerce LLC

FEATURED COMPANIES

  • Accenture
  • Cloudera
  • Hitachi Data Systems
  • Microsoft
  • Platfora
  • Software AG/Terracotta
  • 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. Mind Commerce estimates that global spending on Big Data will grow at a CAGR of 48% between 2014 and 2019. Big Data revenues will reach $135 Billion by the end of 2019.

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, READ MORE >

1 Chapter 1: Introduction

1.1 Executive Summary

1.2 Topics Covered

1.3 Key Findings

1.4 Target Audience

1.5 Companies Mentioned

2 Chapter 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

2.3.1.1 MapReduce

2.3.1.2 HDFS

2.3.1.3 Other Apache Projects

2.3.2 NoSQL

2.3.2.1 Hbase

2.3.2.2 Cassandra

2.3.2.3 Mongo DB

2.3.2.4 Riak

2.3.2.5 CouchDB

2.3.3 MPP Databases

2.3.4 Others and Emerging Technologies

2.3.4.1 Storm

2.3.4.2 Drill

2.3.4.3 Dremel

2.3.4.4 SAP HANA

2.3.4.5 Gremlin & Giraph

2.4 Market Drivers

2.4.1 Data Volume & Variety

2.4.2 Increasing Adoption of Big Data by Enterprises & Telcos

2.4.3 Maturation of Big Data Software

2.4.4 Continued Investments in Big Data by Web Giants

2.5 Market Barriers

2.5.1 Privacy & Security: The 'Big' Barrier

2.5.2 Workforce Re-skilling & Organizational Resistance

2.5.3 Lack of Clear Big Data Strategies

2.5.4 Technical Challenges: Scalability & Maintenance

3 Chapter 3: Key Investment Sectors for Big Data

3.1 Industrial Internet & M2M

3.1.1 Big Data in M2M

3.1.2 Vertical Opportunities

3.2 Retail & Hospitality

3.2.1 Improving Accuracy of Forecasts & Stock Management

3.2.2 Determining Buying Patterns

3.2.3 Hospitality Use Cases

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

3.4 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 & Risk Profiling

3.5.2 Merchant-Funded Reward Programs

3.5.3 Customer Segmentation

3.5.4 Insurance Companies

3.6 Healthcare & Pharmaceutical

3.6.1 Drug Development

3.6.2 Medical Data Analytics

3.6.3 Case Study: Identifying Heartbeat Patterns

3.7 Telcos

3.7.1 Telco Analytics: Customer/Usage Profiling and Service Optimization

3.7.2 Speech Analytics

3.7.3 Other Use Cases

3.8 Government & Homeland Security

3.8.1 Developing New Applications for the Public

3.8.2 Tracking Crime

3.8.3 Intelligence Gathering

3.8.4 Fraud Detection & Revenue Generation

3.9 Other Sectors

3.9.1 Aviation: Air Traffic Control

3.9.2 Transportation & Logistics: Optimizing Fleet Usage

3.9.3 Sports: Real-Time Processing of Statistics

4 Chapter 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 & Business Process Management (BPM)

4.6 Data Governance

5 Chapter 5: Key Players in the Big Data Market

5.1 Vendor Assessment Matrix

5.2 Apache Software Foundation

5.3 Accenture

5.4 Amazon

5.5 APTEAN (Formerly CDC Software)

5.6 Cisco Systems

5.7 Cloudera

5.8 Dell

5.9 EMC

5.10 Facebook

5.11 GoodData Corporation

5.12 Google

5.13 Guavus

5.14 Hitachi Data Systems

5.15 Hortonworks

5.16 HP

5.17 IBM

5.18 Informatica

5.19 Intel

5.20 Jaspersoft

5.21 Microsoft

5.22 MongoDB (Formerly 10Gen)

5.23 MU Sigma

5.24 Netapp

5.25 Opera Solutions

5.26 Oracle

5.27 Pentaho

5.28 Platfora

5.29 Qliktech

5.30 Quantum

5.31 Rackspace

5.32 Revolution Analytics

5.33 Salesforce

5.34 SAP

5.35 SAS Institute

5.36 Sisense

5.37 Software AG/Terracotta

5.38 Splunk

5.39 Sqrrl

5.40 Supermicro

5.41 Tableau Software

5.42 Teradata

5.43 Think Big Analytics

5.44 Tidemark Systems

5.45 VMware (Part of EMC)

6 Chapter 6: Market Analysis

6.1 Big Data Revenue: 2014 - 2019

6.2 Big Data Revenue by Functional Area: 2014 - 2019

6.2.1 Supply Chain Management

6.2.2 Business Intelligence

6.2.3 Application Infrastructure & Middleware

6.2.4 Data Integration Tools & Data Quality Tools

6.2.5 Database Management Systems

6.2.6 Big Data Social & Content Analytics

6.2.7 Big Data Storage Management

6.2.8 Big Data Professional Services

6.3 Big Data Revenue by Region 2014 - 2019

6.3.1 Asia Pacific

6.3.2 Eastern Europe

6.3.3 Latin & Central America

6.3.4 Middle East & Africa

6.3.5 North America

6.3.6 Western Europe

List of Figures

Figure 1: The Big Data Value Chain

Figure 2: Big Data Vendor Ranking Matrix 2013

Figure 3: Big Data Revenue: 2013 - 2019 ($ Million)

Figure 4: Big Data Revenue by Functional Area: 2013 - 2019 ($ Million)

Figure 5: Big Data Supply Chain Management Revenue: 2013 - 2019 ($ Million)

Figure 6: Big Data Supply Business Intelligence Revenue: 2013 - 2019 ($ Million)

Figure 7: Big Data Application Infrastructure & Middleware Revenue: 2013 - 2019 ($ Million)

Figure 8: Big Data Integration Tools & Data Quality Tools Revenue: 2013 - 2019 ($ Million)

Figure 9: Big Data Database Management Systems Revenue: 2013 - 2019 ($ Million)

Figure 10: Big Data Social & Content Analytics Revenue: 2013 - 2019 ($ Million)

Figure 11: Big Data Storage Management Revenue: 2013 - 2019 ($ Million)

Figure 12: Big Data Professional Services Revenue: 2013 - 2019 ($ Million)

Figure 13: Big Data Revenue by Region: 2013 - 2019 ($ Million)

Figure 14: Asia Pacific Big Data Revenue: 2013 - 2019 ($ Million)

Figure 15: Eastern Europe Big Data Revenue: 2013 - 2019 ($ Million)

Figure 16: Latin & Central America Big Data Revenue: 2013 - 2019 ($ Million)

Figure 17: Middle East & Africa Big Data Revenue: 2013 - 2019 ($ Million)

Figure 18: North America Big Data Revenue: 2013 - 2019 ($ Million)

Figure 19: Western Europe Big Data Revenue: 2013 - 2019 ($ Million)

- Accenture
- Adaptive
- Adobe
- Amazon
- Apache Software Foundation
- APTEAN (Formerly CDC Software)
- BoA
- Bristol Myers Squibb
- Brooks Brothers
- Centre for Economics and Business Research
- CIA
- Cisco Systems
- Cloud Security Alliance (CSA)
- Cloudera
- Dell
- EMC
- Facebook
- Facebook
- GoodData Corporation
- Google
- Google
- Guavus
- Hitachi Data Systems
- Hortonworks
- HP
- IBM
- Informatica
- Intel
- Jaspersoft
- JPMC
- McLaren
- Microsoft
- MongoDB (Formerly 10Gen)
- Morgan Stanley
- MU Sigma
- Netapp
- NSA
- Opera Solutions
- Oracle
- Pentaho
- Platfora
- Qliktech
- Quantum
- Rackspace
- Revolution Analytics
- Salesforce
- SAP
- SAS Institute
- Sisense
- Software AG/Terracotta
- Splunk
- Sqrrl
- Supermicro
- Tableau Software
- Teradata
- Think Big Analytics
- Tidemark Systems
- T-Mobile
- TomTom
- US Xpress
- VMware (Part of EMC)
- Vodafone

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