You are a manager in a large information systems consulting company, managing 10 employees in Reno, who each worked 50 weeks, 40 hours per week, (or a total of 2000 hours) in 2019. You want to better understand how your employees spent their time in the calendar year 1/1/19-12/31/19. Specifically, you want to be able to calculate the following: how much time each employee spent on a series of 3 special projects during 2019.
what percentage of total hours worked was on special projects and on regular hours in 2019 how many years they have worked for the company.
You request a report from the Project Management Office, which keeps track of employee information and hour worked. You immediately receive back the following report:
2019 Hours Worked Report (1/1/19-12/31/20)
Hours Worked On Special Projects Regular
Employee Name Dept Plant Sourcing Production Quota Hours
Review Planning Computation Worked (*)
Casimiro, Amanda Ops Reno 300 200 500 1000
McGovern, Adrian Acct Reno 500 500 600
Menstell, Lori Lee Mkt Reno 300 200 100 1400
Jefferies David Mkt Reno 400 500 222 878
Nurul, Nicole Mkt Reno 300 700 500 500
Garrett, James Ops Reno 100 100 100 1700
Austin, James Sales Vegas 500 100 100 1300
Redmond, Elizabeth Mkt Reno 200 300 600 900
Daniel, James Sales Reno 500 500 500 500
Mei Ling Garcia Acct Reno 800 200 500 500
Menstell, Lorie Lee Mkt Reno 0 500 100 1400
(*) For each employee, Regular Hours Worked + Hours Worked On Special Projects = Total Hours Worked
Identify ALL potentially questionable data in the table, and indicate exactly what it is about the piece of data that is questionable . Be as SPECIFIC as possible. Here is an example:
Instead of saying "some data seems wrong", you might say "the value "941310" is listed as a zip code, but zip codes consist of 5 digits, whereas this value has 6 digits.
For each data integrity characteristics (accuracy, timeliness, relevance, sufficient, worth it) describe whether the data in the table satisfies that data integrity characteristic.