Pivot table and visualization

Mell Industries hire you as data scientist. For you first assignment; Ms. Forward, your boss; asked you to use a file (Case_DataSet.xlsx) regarding salaries in the company to answer the following questions:

1. Which occupation has been terminated due to a low ‘total evaluation score”? What is the average overall evaluation score for those occupations terminated? What is the average job duration for that occupation in 2017?

2. Why do you think there is a turnover rate for this occupation described in question 1?

3. How many male employees were making more (percentage wise) than female employees in the $50,001 - $100,000 salary bracket?

4. Employees Evaluation Metrics. Employees are subject to performance evaluations every year based on five different criteria: Knowledge of work, communication skills, teamwork, leadership, and quality of work. Each employee supervisor assess each employee and prepares a performance report. Based on this performance reports, what can be said about the top ten highest paid positions? Are the employees being paid fairly based on their evaluation scores? What might be a factor for salary discrepancies?

5. What would be your recommendations to prevent high turnover rates and to solve any salary inconsistences for each position?

Using Tableau

1. For the following positions, design a chart to compare the average salaries of males and females employees:

· Administrator Purchasing

· Assoc Will Call Center

· Business Specialist

· Category Manager

· Merchandiser

· Sr Eng App Developer

· Stocking Associate

· Warehouse Supervisor

2. Design a chart to represent the difference between the highest paid male and female salaries, along with their evaluation scores.

Ms. Forward wants you to submit thee documents. The Excel file with your data, data preparation, and data analysis. A PDF with the Tableau charts, and a Word document with your detailed description on how you answer each one of the questions and how you designed and built the Tableau charts. If there is missing information, Ms. Forward wants you to state what is missing and how you can overcome that weakness on the data.