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Subscriber Data Management (SDM) Meets Big Data: Opportunities for Wireless Carriers 2014 - 2018

 

Albany, NY -- (SBWIRE) -- 07/15/2014 -- Report Audience

Big Data Companies
Mobile Cellular Carriers
Wireless Device Manufacturers
Wireless Infrastructure Providers
Commerce, Content and Application Providers

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Report Overview

Wireless carriers utilize Subscriber Data Management (SDM) systems to consolidate data in a single virtual data store with centralized administration, management and reporting. The “Big” part of Big Data comes from the fact that it is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools. However, Big Data is also unstructured, meaning that it does not have a pre-defined data model or is not organized in a pre-defined manner. These two things taken together make Big Data a big challenge, but also a big opportunity for wireless carriers with SDM.

This report focuses on the opportunities for wireless carriers to leverage their SDM systems to mine Big Data, perform analytics, and gain business intelligence. The report covers the opportunities for wireless carriers to leverage intelligence gained for various new market opportunities such as selling data to trusted third parties and other business-to-business ventures that incremental to their traditional lines of business.

Table of Contents

1. Introduction
1.1. Subscriber Data Management
1.2. Big Data = Unstructured Data
1.3. Why SDM + Big Data

2. Wireless Carriers and SDM
2.1. Sources of Unstructured Data
2.2. Mining Data from SDM

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3. Related Wireless Carrier OSS and Performance Systems
3.1. Operational Support Systems (OSS)
3.2. Self-organizing Networks (SON)
3.3. Network Monitoring Systems

The report provides key assessment of important issues such as data quality, integrity, security, and privacy. Key issues such as Data Anonymization are addressed along with the benefits and potential pitfalls. The report includes forecasts for 2014 – 2018 for wireless carrier investment in analytics as well as overall Big Data revenue.

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