The potential employer would like you to conduct an analysis of data and then summarize your findings using clear language for a nontechnical audience. They have provided you with a data set called FleetMaintenanceRecords to base your report on for the interview. They have asked you to identify relevant themes that can be used to help them manage their fleet of trucks. In preparation for your interview, create an example summary of the analysis you conducted that you would use to communicate the findings to stakeholders. Place the deliverables for your instructor and the potential employer in the Analysis and Summary Template. Analyze the data you’ve been provided to identify themes. Guiding information to gather:
Review part-replacement frequencies and types and create a hypothesis that can be used by the fleet management team to better deal with vehicle maintenance. You’ll need to create a table called Parts Maintenance and load the data into it. Put this table in the database named after yourself. Load this data set from the ‘/home/codio/workspace’ path and run queries to find the results.
Which parts are being replaced most?
Is there a region of the country that experiences more part failures and replacements than others?
Can you identify a region (Northeast, Southeast, Midwest, Northwest, Southwest) that has more reasons for replacement? Use the Region Definitions sheet to identify states in each region.
How might the fleet maintenance team use the information to update its maintenance schedule? Your response should be backed by the data you have found.
Which parts are being replaced most due to corrosion or rust?
Which parts are being replaced because of mechanical failure, like a flat tire or rock through the windshield?