Global Technology Trends Report: Big Data and Extreme Info Processing

Big Data represents more than just a collection of data sets that form a large quantity of data, which is difficult to process using traditional data processing applications. Big Data also represents a big business opportunity across many industry verticals.

Global Technology Trends Report: Big Data and Extreme Info Processing provides comprehensive analysis of big data in several key industry verticals including healthcare, government and telecommunications. The report evaluates global big data trends including anticipated applications in across industry verticals and companies developing solutions. The report evaluates the future of big data management, analytics, and related issues. The report also provides a market outlook and recommendations for big data business developers.

Target Audience:

  • Government
  • Healthcare organizations
  • Military and Homeland Security
  • Telecommunications companies
  • Data storage and processing companies
  • Research and development organizations
Companies in Report:

General Methodology

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.

Forecasting Methodology

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.

1.0 Executive Summary
2.0 Introduction
2.1 What Is Big Data?
2.1.1 Volume
2.1.2 Variety
2.1.3 Velocity
2.2 Big Data Categories
2.2.1 Structured Big Data
2.2.2 Un-structured Data
2.2.3 Semi-structured Data
2.3 Why Is It Important?
2.3.1 Pattern Discovery
2.3.2 Decision Making
2.3.3 Process Invention
2.3.4 Increasing Revenue
2.4 Big Data Growth Drivers
2.5 Big Data Technology
2.5.1 Sensors
2.5.2 Computer Networks
2.5.3 Data Storage
2.5.4 Cluster Computer Systems
2.5.5 Cloud Computing Facilities
2.5.6 Data Analysis Algorithms
3.0 Big Data In Healthcare
3.1 Big Data Challenges In Healthcare
3.1.1 Healthcare As A Technology Laggard
3.1.2 Integration
3.1.3 Security
3.1.4 Standards
3.1.5 Real-time Processing
3.2 Big Data Applications In Healthcare
3.2.1 Real-time Monitoring Applications
3.2.2 Healthcare Data Warehousing Applications
3.2.3 Healthcare Data Exchange Applications
3.3 Healthcare Big Data Opportunities
3.3.1 Patients
3.3.2 Providers
3.3.3 Researchers
3.3.4 Pharma
3.3.5 Medical Device Companies
3.3.6 Payers
3.3.7 Governments
3.3.8 Software Developers
3.4 Healthcare Big Data Companies
3.4.1 Explorys
3.4.2 Humedica
3.4.3 Intersystems
3.4.4 Pervasive
4.0 Government
4.1 Big Data Government Applications
4.1.1 Administration Interaction Applications
4.1.2 Services
4.1.3 Personalizing
4.2 Government Big Data Companies
4.2.1 Netapp
4.2.2 Cataphora
5.0 Telecommunications
5.1 Big Data Telecommunications Applications
5.1.1 Data Collection And Mining
5.1.2 Targeted Product And Marketing Offers
5.1.3 Network Optimization
5.2 Companies For Telecommunications Big Data Applications
5.2.1 Pervasive
5.2.2 Amanzitel
6.0 Future Of Big Data
6.1 Parallel Technology Advance
6.2 Multi-platform
6.3 Self-serve
6.4 Collaboration
6.5 More Real-time
6.6 Privacy And Security Issues
6.7 Expanding In Mobile Market
6.8 Location-based Information
7.0 Summary And Recommendations

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