Think BIG, Act SMALL: Use Case Series – Part 4 of 5 (Using Big Data in Telecommunications and Media & Entertainment)

Aug 17

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Big Data use-cases in Telecommunications

In recent decade, telecom industry has seen data explosion due to increase in subscription, voice data record, wireless information, geo-location details, social media and data usages. Telecom companies who used legacy systems to gain insights from internally generated data often face issues of high storage costs, long data loading time, long administration process, complex queries, outdated compression techniques, and high support costs.   Many organizations are beginning to wake to the reality of big data. Here are some of the use cases for Big Data in Telco business.

1. Revenue assurance and price optimization

2. Customer churn prevention

3. Campaign management and customer loyalty

4. Call Detail Record (CDR) analysis

5. Network performance and optimization

6. Mobile User Location analysis

Big Data use-cases in Media & Entertainment

The media/entertainment industry moved to digital recording, production, and delivery in the past few years and is now collecting large amounts of rich content and user viewing behaviors on real-time basis. Few of the use cases are listed below:

1. Campaign management

2. Customer Sentiment Analysis

3. Customer Behavior Analysis

4. Ad targeting (search, display, mail)

5. Website optimization

6. Yield optimization

7. Click-through analysis

8. Click fraud analysis

9. Network usage analysis

Next time: Part 5 of 5 (Using Big Data in Utilities, Hi-Tech and ECommerce)

About Author:

Sushil Pramanick is the Vice President – Analytics and Information Management (AIM Practice) with Encore Software Services. Sushil is a BI industry thought leader and a Big data champion. To know more about our Big data offerings and capabilities, visit us at http://www.EncoreSS.com or email at spramanick@encoress.com. You can also reach him at 949 391 8520 and follow him on his twitter @Pramanicks. Feedback, comments and suggestions are welcome!

About Sushil Pramanick

Sushil is a Technology Executive for Business Analytics & Optimization Practice with IBM. Sushil specializes in big data and analytics, business intelligence, enterprise data warehouse, data governance/MDM and enterprise architecture. He has over 18 years of industry experience in retail, banking/financial, healthcare, manufacturing, high-tech, telecom and M&E. Sushil has various certifications from IBM, Oracle, QAI, PMI and others. He holds a master's degree in finance and accounting from the Institute of Chartered Accountants of India with a bachelor's degree in accounting from the University of Mumbai, India. He has done speaking engagements at Text Analytics conference and also as a media partner for IE conferences on various analytics, big data and BI topics. Find his profile on LinkedIn @ www.linkedin.com/in/pramanicks and follow him on Twitter @pramanicks. These comments and views are my own personal opinions only and do not necessarily reflect the positions or opinions of my employer (IBM) or their affiliates and partners. All comments are based upon my current knowledge and my own personal experiences. You should conduct independent tests to verify the validity of any statements made in this blog before basing any decisions upon those statements. In addition, any views or opinions expressed by visitors to this blog are theirs and do not necessarily reflect mine.

Posted on August 17, 2012, in Apache Hadoop, Big Data Analytics, Business Intelligence and tagged , , , , , , , , , , , , . Bookmark the permalink. 1 Comment.

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