We instinctively know that clean data = quality data. However, it is important to understand how...

We instinctively know that clean data = quality data. However, it is important to understand how data that has not been cleansed can negatively impact business decisions.

a. Share your interpretation of data cleansing. Use your own words and avoid overly complex explanations.

b. Describe at least 3 decisions a business with which you are familiar (either through your work or your research) may make as a result of data mining.

c. Discuss the negative impact of data that has not been cleansed would have on these decisions.

Be sure to:

Answer each part of the question
Cite and reference as appropriate

Expert Solution

1. When we get the data it may not be directly ready for the analysis thus there could be the following problems in the data.

It could be incorrect
It could be incomplete
It could be irrelevant
It could be duplicated
It could be improperly formatted.

Thus due to these problems we need our data to be clean which can help us to train our models and generate correct information out of it. Thus data cleaning is required for the data.

2. There are the following companies which are making a profit out of data mining

Video Streaming companies: These companies use data which we generate in order to analyze the likes and dislikes and in turn show us the content which we may like. Thus in this way, they can increase their profit.
recommendation of products: Ecommerce websites use this data in order to suggest new products based on our previous likes and dislike.
Restaurant recommendation: So they recommend new restaurants based on our previous like and dislike, the rating which we gave for them.

3. The data which is not cleansed can also be called as dirty data and this is data which can cause the revenue to fall a lot and sometimes it can take away reputation of the company. Also if the data is dirty we may be doing work unnecessary and maybe in wrong direction.
Thus in order to start in the correct direction, we may have less cleased data but we should not start our findings with dirty data

That was a nice question to answer
Friend, If you have any doubts in understanding do let me know in the comment section. I will be happy to help you further.
Thanks

venereology answered 1 year ago

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