The Big Data Market: 2015 – 2030 - Opportunities, Challenges, Strategies, Industry Verticals and Forecasts

“Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years. Big Data not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data to solve complex problems.

Amid the proliferation of real time data from sources such as mobile devices, web, social media, sensors, log files and transactional applications, Big Data has found a host of vertical market applications, ranging from fraud detection to scientific R&D.

Despite challenges relating to privacy concerns and organizational resistance, Big Data investments continue to gain momentum throughout the globe. SNS Research estimates that Big Data investments will account for nearly $40 Billion in 2015 alone. These investments are further expected to grow at a CAGR of 14% over the next 5 years.

The “Big Data Market: 2015 – 2030 – Opportunities, Challenges, Strategies, Industry Verticals & Forecasts” report presents an in-depth assessment of the Big Data ecosystem including key market drivers, challenges, investment potential, vertical market opportunities and use cases, future roadmap, value chain, case studies on Big Data analytics, vendor market share and strategies. The report also presents market size forecasts for Big Data hardware, software and professional services from 2015 through to 2030. Historical figures are also presented for 2010, 2011, 2012, 2013 and 2014. The forecasts are further segmented for 8 horizontal submarkets, 15 vertical markets, 6 regions and 35 countries.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

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
2.3 Key Characteristics of Big Data
2.4 Market Growth Drivers
2.5 Market Barriers
　 　
3 Chapter 3: Vertical Opportunities & Use Cases for Big Data
3.1 Automotive, Aerospace & Transportation
3.2 Banking & Securities
3.3 Defense & Intelligence
3.4 Education
3.5 Healthcare & Pharmaceutical
3.6 Smart Cities & Intelligent Buildings
3.7 Insurance
3.8 Manufacturing & Natural Resources
3.9 Web, Media & Entertainment
3.10 Public Safety & Homeland Security
3.11 Public Services
3.12 Retail & Hospitality
3.13 Telecommunications
3.14 Utilities & Energy
3.15 Wholesale Trade
　 　
4 Chapter 4: Big Data Industry Roadmap & Value Chain
4.1 Big Data Industry Roadmap
4.2 The Big Data Value Chain
　 　
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
5.6 Vertical Market Case Studies
　 　
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
7.3 Vertical Market Segmentation
7.4 Regional Outlook
7.5 Asia Pacific
7.6 Eastern Europe
7.7 Latin & Central America
7.8 Middle East & Africa
7.9 North America
7.10 Western Europe
　 　
8 Chapter 8: Vendor Landscape
　 　
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