Big Data in Government, Defense and Homeland Security 2015 - 2020
Global governments see a range of opportunities in terms of defense, security, and public safety related improvements possible by leveraging massive amounts of data available in modern society. The US Government in particular sees data of various types (structured and unstructured) and from various sources as an opportunity to continuously improve predictive capabilities regarding its defense and homeland security programs.
For Homeland Security, Predictive Analytics and Predictive Policing are rapidly becoming critically important tools, especially to military operations, counterterrorism, and disaster mitigation and recovery strategies. In 2015 alone, about US$333 million is allocated for the advancement of defence and security, in relation to tapping the potential of the Big Data. While the government acknowledges the use of Big Data to improve measures of national defense and homeland security, there is a looming question as to how the government, the civil society and the whole state adapt their interest with Big Data and transform it as a potential and relevant tool to improve the integrity of the national sovereignty.
This research focuses on Big Data and its functional capabilities, applications, and solutions in support of defense and homeland security including data acquisition, collection, detection and prediction. 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.
Big Data companies
Social network companies
Telecom service providers
Public safety organizations
Military and homeland security
Data services and analytics companies
Cloud and telecom infrastructure providers
Big Data in defense and homeland security forecasts through 2020
Understand the role and importance of Big Data mitigating cybercrime
Identify opportunities for Big Data applications, services, and solutions
Identify issues surrounding Big Data security relative to governmental systems
Understand the importance of proactive policy decisions and Big Data solutions
Understand the importance of predictive analysis in import and export of goods
Understand the range of options for Big Data and comprehensive homeland security
Understand the use of Big Data for disaster recovery and counterterrorism operations
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.
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