P2 – Data Mining using RapidMiner October 2018 SEMESTER School of Business & Accountancy (Diploma in Business Practice) (Administration and Management) Certificate in Business Applications BUSINESS ANALYTICS Data Mining Project using RapidMiner Sales & Marketing Analytics – Customers Churn ELBALY (CET) Page 1 of 7 ELBALY_Oct_AY18- FIA
P2 – Data Mining using RapidMiner 1 Final Individual Assignment SingaTel is a local telecommunication providing mobile, internet, TV and fixed line telephony services. This year, SingaTel is concerned about the number of customers leaving and subscribing to its competitors. It needs to understand who is leaving as customer acquisition is a life-and-death matter for most companies, and so are customer retention and its opposite, churn. The Sales & Marketing Director has engaged the analytics team to identify the common and key attributes that contributed to those who have left, likely to leave in the near future, and why. To conduct a data mining analysis, a complete dataset with attributes as shown in Table 1, comprising information on customers who have left the telco since Jan 2017 as well as existing customers, has been made available to you. In this assignment, you are required to by yourself on this data mining project with the help of the RapidMiner product suite. A series of tutorials in RapidMiner are in place to scaffold your learning as you embark on this data mining project. You are required to use the CRISP-DM framework shown below as a guide to complete the project. ELBALY (CET) Page 2 of 7 ELBALY_Oct_AY18- FIA
P2 – Data Mining using RapidMiner 2 Data The dataset ( SingaTel_Customers.xlsx) can be downloaded from the PolyMall portal. Table 1 gives a full description of the dataset including the attributes of the data. Attribute Description Labels/ Values Data Definitions CustomerID Customer number 4-digit by dash and 4letters Gender Customer’s gender Male or Female SeniorCitizen Customer type who is a senior citizen 0, 1 1
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