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Big Data Impacts on Telecom Business

Big Data Impacts on Telecom Business

Leveraging Big Data technologies is driven by the need for additional information derivable from analysis of all of electronic data available to a business. This electronic data is general information available via the Internet combined with the large volumes of data being collected by companies such as major banks, financial companies, telecom operators and other Fortune 500 companies.

This information is a hidden source of business intelligence and customer preferences. Actionable business intelligence derived from this data will help businesses spot business trends and/or determine new or modified business strategies.
This report focuses on Big Data from an ICT/telecom perspective and evaluates issues and costs involved in migrating to Big Data technology. This report also evaluates challenges and opportunities. It also presents specific recommendations for telecom service providers regarding Big Data applications and benefits.

Target Audience:

  • Big Data companies
  • Telecom service providers
  • Customer services companies
  • Data services and analytics companies
  • Cloud and telecom infrastructure providers


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.


Introduction
Big Data Overview
Technology Trends
Big Data Transition Challenges
Opportunities
Risks And Issues
Summary And Recommendations

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