The Big Data Market: Business Case, Market Analysis & Forecasts 2015 - 2020
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 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 chain analysis, case studies and a quantitative assessment of the industry with forecasting from 2015 to 2020.
Topics covered in the report:
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
Vendor Assessment and Key Player Profiles: 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 the Big Data market from 2015 to 2020
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- Investment Firms
- Media Companies
- Utilities Companies
- Financial Institutions
- Application Developers
- Government Organizations
- Retail & Hospitality Companies
- Other Vertical Industry Players
- Analytics and Data Reporting Companies
- Healthcare Service Providers & Institutions
- Fixed and Mobile Telecom service providers
- Infrastructure, Software, and Service Vendors
- Big Data opens a vast array of applications & opportunities in multiple vertical sectors including not limited to retail & hospitality, media, utilities, financial services, healthcare and pharmaceutical, telecommunications, government & homeland security and the emerging industrial internet vertical. We see certain verticals leading the way in terms of best practices including optimized data collection, analysis, and reporting.
- 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 46% between 2015 and 2020. Big Data revenues will reach $190 Billion by the end of 2020.
- Detailed forecasts 2015 – 2020
- 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 and Organizations in Report:
- Actuate Corporation
- Apache Software Foundation
- APTEAN (Formerly CDC Software)
- Bank of America
- Bill & Melinda Gates Foundation
- Booz Allen Hamilton
- Bristol Myers Squibb
- Brooks Brothers
- Carnegie Corporation
- Centre for Economics and Business Research
- Cisco Systems
- Cloud Security Alliance (CSA)
- Cloud Standard Customer Council
- Computer Science Corporation
- Data Direct Network
- General Electric
- General Electric Capital
- GoodData Corporation
- Harley Davidson
- Hitachi Data Systems
- International Standards Organization (ISO)
- International Telecommunications Union (ITU)
- JP Morgan Chase
- Juniper Networks
- McLaren Racing Team
- MongoDB (Formerly 10Gen)
- Morgan Stanley
- MU Sigma
- New Classrooms Innovation Partners
- National Institute of Standards & Technology (NIST)
- Open Data Center Alliance
- Open Data Foundation (ODaF)
- Opera Solutions
- Renaissance Learning
- Revolution Analytics
- Rockwell Automation
- SAS Institute
- Sherwin Williams
- Software AG/Terracotta
- Tableau Software
- Tata Consultancy Services
- Think Big Analytics
- Tidemark Systems
- US Federal Government (various agencies and departments)
- US Xpress
- VMware (Part of EMC)
Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.
We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.
In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.
We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.
We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.
Step 1 - Forecasts Input:
The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.
Step 2 - Forecasting of Future Years:
Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.
Step 3 - Validation of Data:
The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.