Pewlett-Hackard-Analysis

Module 7

Overview of the analysis.

• Determine, identify and analyze data using SQL.

• Create queries that use data to answer questions using database which are nowadays used everywhere.

Results:

1- Retirement titles table

• The table was used to identify the titles of the people about to retire.

• It actually has more entries than the number of people because some people have changed titles.

• This table needs to be cleaned further to be used for proper analysis.

2- Unique titles

• Actually indicates the people that will retire.

• The results suggest that 30% of the pople will retire (90,398/300,024). Now the analysis becomes cleaner as it actually identifies data to be analyzed and to be taken into consideration for a closer look and action.

3- Retiring titles

• Below are the titles that will retire and what should be the focus of HR team.

count title

29414 Senior Engineer

28254 Senior Staff

14222 Engineer

12243 Staff

4502 Technique Leader

1761 Assistant Engineer

2 Manager

• Recruiting or training etc. should be focused on the dimensions of this positions that will be in more demand.

4- Mentorship eligibility

• This data suggests that less than 2% of titles to be replaced are eligible for mentoring programs.

• Clearly better mentoring is needed and perhaps the criteria and the mapping of the mentoring program to the titles replaced, needs to be reviewed to match the demands at Pewlett Packard

Summary:

• Based on the results, the two queries or tables that may provide additional insight are as below:

1- Query and table to show the people ahead of retirement time as milestone that would trigger mentorship programs so that the retirement date would match new people mentored or ready for work as per HR policies and matrixes.

2- More titles that will retire can be eligible for mentorship. Direct quota increase or criterias that allow more retiring titles to be eligible for mentorship.