Big data Case Study : The problem is to reduce churn ratio by 5% quarterly by an
ID: 3823370 • Letter: B
Question
Big data Case Study: The problem is to reduce churn ratio by 5% quarterly by analyzing CDR, credit report and billing data of telecom operators to mine out churn trends of a specific region or a specific person or and age group.
Questions:
1. Which tools on Slide 12 might you use to describe you metadata? (slide# 12 attached below)
Metadata Models Formats UML/RDF/OWL conceptual XML/JSON hierarchical MPEG file format Standards NIEM Law Enforcement, Social Services METS-Library MPEG-Media RDF SOA HL7 Health Data DICOM-Health Imaging AIXM/WIXM/FIXM-Aero Information Exchange Slide 12Explanation / Answer
Answer:
In the tools mentioned you can use XML/JSON tool to determine the churn trends.This automatically extracts preservation-related metadata from digital files
output that metadata in a standard format (XML) for use in preservation activities.
Churn Management :
Current global economical challenges leads to the reduction of customer's buying power and indirectly this affects your sales. Changes in the business models is needed to prevent churn.
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