Big Data and Telecom Analytics Market: Industry Trends, Size, Share, Growth, Analysis and Forecast REsearch Report Available Online By ResearchMoz.us
Albany, NY (PRWEB) November 29, 2013
Big Data refers to a massive volume of both structured and unstructured data that is so large that it is difficult to process using traditional database and software techniques. While the presence of such datasets is not something new, the past few years have witnessed immense commercial investments in solutions that address the processing and analysis of Big Data.
Big Data opens a vast array of applications and opportunities in multiple vertical sectors including, but not limited to, retail and hospitality, media, utilities, financial services, healthcare and pharmaceutical, telecommunications, government, homeland security, and the emerging industrial Internet vertical.
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With access to vast amounts of data sets, telecommunications companies are emerging as major proponents of the Big Data movement. Big Data technologies, and in particular their analytics abilities, offer a multitude of benefits to telecom companies including improved subscriber experience, building and maintaining smarter networks, reducing churn, and generation of new revenue streams.
Mind commerce, thus expects the Big Data driven telecom analytics market to grow at a CAGR of nearly 50% between 2014 and 2019. By the end of 2019, the market will eventually account for $5.4 Billion in annual revenue.
This report provides an in-depth assessment of the global Big Data and telecom analytics markets, including a study of the business case, application use cases, vendor landscape, value chain analysis, case studies and a quantitative assessment of the industry from 2013 to 2019.
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Topics covered in the report include:
The Business Case for Big Data: An assessment of the business case, growth drivers and barriers for Big Data
Big Data Technology: A review of the underlying technologies that resolve big data complexities
Big Data Use Cases: A review of investments sectors and specific use cases for the Big Data market
The Big Data Value Chain: An analysis of the value chain of Big Data and the major players involved within it
Big Data in Telco Analytics: How telecom can utilize Big Data technology to reduce churn, optimize their networks, reduce risks and create new revenue streams
Telco Case Studies: Case Studies of two major wireless telecom capitalizing on Big Data to reduce churn and improve revenue
Vendor Assessment & Key Player Profiles: An assessment of the vendor landscape for leading players within the Big Data market
Market Analysis and Forecasts: A global and regional assessment of the market size and forecasts for the Big Data market from 2014 to 2019
Retail & Hospitality Companies
Other Vertical Industry Players
Analytics and Data Reporting Companies
Healthcare Service Providers & Institutions
Fixed and Mobile Telecom service providers
Big Data Technology/Solution (Infrastructure, Software, Service) Vendors
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Companies in Report:
Apache Software Foundation
APTEAN (Formerly CDC Software)
Bristol Myers Squibb
Centre for Economics and Business Research
Cloud Security Alliance (CSA)
Hitachi Data Systems
MongoDB (Formerly 10Gen)
Think Big Analytics
VMware (Part of EMC)
Related Reports -
Big Data Market - Global Scenario, Trends, Industry Analysis, Size, Share And Forecast 2012 - 2018
“Big Data Market – Global Scenario, Trends, Industry Analysis, Size, Share and Forecast, 2012 – 2018″ the global big data market was worth USD 6.3 billion in 2012 and is expected to reach USD 48.3 billion by 2018, at a CAGR of 40.5% from 2012 to 2018. North America is expected to maintain its lead position in terms of revenues till 2018, with about 54.5% share of the global big data market revenue, followed by Europe.
Generation of huge amounts of data, called big data, across different sectors such as banking, healthcare, retail and education, among others, is creating the need for an efficient tool to manage this data. Conventional database management tools such as Relational Database Management System (RDBMS) do not have the capability to manage surging volumes of unstructured data.
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