The excel file “cases-rawdata.xls” contains raw data logged in an online helpdes

Question

The excel file “cases-rawdata.xls” contains raw data logged in an online helpdesk system. The “cases” worksheet contains information on questions, including case ID, who submitted the question and when, when the question was closed, description of the question, number of replies from an knowledge expert and number of times the question has been forwarded to, etc. The “people” worksheet contains information on characteristics of individuals who submitted questions to the system, including job title, function, organization level, education, employment date, etc.
Based on the raw data, provide your thoughts/comments and what you would do to pre-process the data set.
a) What data issues (such as missing values, inconsistency, outliers, etc) do you observe in the data set?
b) Often times, one needs to combine data from different sources for future analysis. In this particular case, a data analyst would need to combine “cases” with “people” by joining [Logged by] and [name]. How would you do this (execute the
join and combine the two data sources into a single data set with headings in the “combined data” worksheet)?
c) What issues would you expect when you perform the join operations in (b)? What would you do to address those issues?
d) Are you concerned about the performance issues when cleaning the data?

Explanation / Answer

you can combine the cases and people worksheet by using a cluster key that's common Attribute in both the worksheets For example : Here for every problem there must be a person from People who solved it . So, we can decide problem id as cluster key and give details of person who solved it after all the columns of "cases" Of course there will be data redundancy as names will be repeated and not all names will be listed Can try to give more insight .. but pics not that clear .

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