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Overview
The quality of a data set determines whether data analysis successfully addresses an organizational problem. Therefore, data must go through preprocessing before the actual data analysis is performed. It is essential to clean a data set prior to addressing a problem through data analysis. Working out the details of the problem you are trying to address will dictate what data you need and what can be filtered out.
Use the following scenario for this assignment: You work for a small data analytics consulting firm. You’ve been asked to write a post on your company’s blog about cleaning data. In your post, you will compare a tool of your choice to Excel and touch on specific key points. Be sure to include an introduction section detailing the importance of cleaning data.
Prompt
For your blog post, you will examine a few different tools commonly used to clean data. Please choose a tool from the list below to compare with Excel:
SAS
Python
R
MySQL
In your comparison, you must specifically discuss how the the following tasks are completed within each of the tools:
Clearing extra spaces
Converting numbers stored as text into numerals
Removing irrelevant or duplicate data
Fixing structural errors and altering formatting as needed
Filtering unnecessary outliers
Handling missing data
Be sure to keep in mind the following questions:
How is each task completed differently or similarly between the two tools?
Is one tool better than the other for a specific task?
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