Big Data Opportunities, Challenges and Solutions for Industry Verticals
Big data is more than just one of the biggest buzz words in years. It represents a huge business opportunity to leverage arguably the most valuable enterprise asset: data about customers, operations, markets, competitors, and more.
Organizations across nearly every industry find that they not only require to manage growing large data volumes in their real-time systems, but also to analyze that information so they can quickly make more optimal decisions to help them compete more effectively in the marketplace.
Companies across a wide range of industry verticals and market segments are beginning to leverage Big Data and analytics to produce insights from hidden information floating in a sea of raw data that is otherwise too costly to process and discover.
- Learn about Big Data solutions and strategies for enterprise
- Understand the challenges and benefits for enterprise Big Data
- Identify the market opportunities for Big Data in industry verticals
- Learn about Big Data and analytics vendor solutions and strategies
- Big Data companies
- Governmental organizations
- Telecommunications companies
- Analytics and data reporting companies
- Data storage and processing companies
- Research and development organizations
- Cloud infrastructure and service providers
- All industry verticals and market segments
Companies in Report:
- Amazon Web Services
- Computer Science Corp
- Data Mining Research
- General Electric
- Globe Telecom
- McKinsey Global
- Programmable Web
- Tata Consultancy Services
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.