Homework 3 – Data Preparation Objectives: Master data preparation concepts and

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Homework 3 – Data Preparation
Objectives:
Master data preparation concepts and

Homework 3 – Data Preparation
Objectives:
Master data preparation concepts and apply the methods with a real-world data set
Practice how to perform data preparation with RapidMiner software
Descriptions
In the homework, you will find a real-world data set of your choice, pose a research question, and then apply data preparation/scrubbing with RapidMiner software, if necessary, to answer your research question.
Instructions:
1. Find a data set of your choice (or you can directly use catalog.csv, raw-customer-churn-data.csv on Blackboard). Keep in mind the chosen data set should have at least 50 observations. You may not use any dataset that is used in a RapidMiner demo, posted on the web.
2. Based on your chosen data set, pose your research question.
3. Import your data set into RapidMiner, and drag the data set into the Process window. Run the process and examine your data set.
4. Does your data set have missing values? Does your data set have inconsistent values? Is it appropriate to reduce the number of attributes in your data set? Is it appropriate to reduce the number of observations? Perform applicable data scrubbing/preparation activities and explain whether or not the activities applied help answer your research question.
Reflection:
Summarize what you did and reflect on the roles of your data preparation/scrubbing activities in answering your research question.
ITMG 516
NAME: DATE:
HOMEWORK #:
RESEARCH QUESTION:
DATA SET SOURCE:
NUMBER OF COLUMNS:
NUMBER OF ROWS:
SCREENSHOTS:

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