I am working at Vodafone,Dwh Reengineering Project as a consultant. My interests are Data Engineering, Architectural Design of BI Projects, Developing DWH Applications. I skilled in Data Warehousing, Business Intelligence, Data Integration.

useR! 2019 Toulouse

Lightning Talk - Methods&Applications

With this lightining talk, We learn different methods and applications that is told from different participants.One of them is Megan Beckett.She is from Cape Town South America. She is data scientist at exegetic analytics.Megan Beckett mentions about spatial optimisation with OSRM and R.Osrm package is an interface beetween R and the OSRM API. This package allows to compute distances (travel time and kilometric distance) between points and travel time matrices.So you can find the perfect running route.The other participant is Angeline Protacio.Her project is using R and the Tidyverse to aid decision-making for drafting batters in fantasy baseball.

Churn Prediction in Telecom Industry Using R

Churn prediction is very important for telecom sector as it is in every sector. Prediction of customers who want to churn, you can create specific campaigns to them to reduce the revenue loss of the company.This research is using data mining technique and R package to predict the results of churn customers on the benchmark Churn dataset.

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Estimating individual Customer Lifetime Values with R

Valuing customers is key to any firm. Customer lifetime value (CLV) is the central metric for valuing customers. It describes the long-term economic value of customers and gives managers an idea of how customers will evolve over time. The customer lifetime value as described here is a useful metric for the telecom provider to make customer selections and, after applying it to other business products, it could be used to discriminate between product offers.

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R Data Analysis Projects: Introducing Content-Based Recommendation

There is lots of mobile product and services in telecommunication sector.It is difficult to choose the right product for the customer day by day. Recommender systems give them helpful recommendations of various products and services.It is possible to build recommndation system using R.

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