Securing Big Data Infrastructure: An Evolving Market Ecosystem
The Big Data industry is experiencing profound changes across the entire stack including infrastructure, security, analytics, and application layer. The data management industry is shifting from host based architecture to cloud based data centric architecture and operational model, thereby creating enormous challenges on infrastructure security.
This creates an evolving market ecosystem for Big Data technology and services, infrastructure, and security solutions, software solutions, and support services. Open source solutions such as Hadoop, Cassandra, and MongoDB play a key role in the ecosystem in terms of security features. However, full infrastructure security involves initiatives of many players including general security solution providers.
This research evaluates the components of Big Data infrastructure and security framework along with security challenges related with Hadoop, Cassandra, and MongoDB. This research also analyzes the Big Data infrastructure security market ecosystem, components associated with strategic framework for Big Data protection, and vendor solution landscape.
The report also includes market projection for enterprise spending on Big Data technology and services encompassing three verticals. Forecasting includes market projections by industry verticals and geographic region. 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.
Certain industries will be drivers of Big Data Security
Big Data infrastructure will require strategic governance and framework for security
Big Data infrastructure and security solution market spending alone will reach $23.7 billion by 2021
The evolving Big Data Security ecosystem consists of infrastructure, applications, APIs, and data itself
Big Data Security should be a key part of strategy within the Big Data Lifecycle Management (BDLM) model
Big Data vendors
Big Data security providers
Telecom equipment providers
Global infrastructure suppliers
Communication service providers
Cloud services and datacenter companies
Big Data consulting, and advisory companies
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.