Manasi Shidhaye

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Introduction

As an Analytics onsultant, explored NYC buses data to determine common delay or breakdown reasons, delay times as per companies as well as explored the correlation between specific days of the week and the frequency of breakdown or delays.

Business Questions

1. What are the common Delay Reasons?
2. What are the longest delay times?
3. Which products will perform best at the new location(s)?

Insights

• Majority of the bus breakdowns were due to mechanical problems.
• Regular servicing and maintainence can help save this problem.
• Buses were running late due to heavy traffic during peak times.
• A suggestion would be to pick up scchool students at non peak traffic times.
• COmpanies were sorted according to the highest delay times.
• A decline was found in the breakdowns as the week progressed from Monday towards Fridays.

Data Source:

This was a guided project as part of the Data Analyst Bootcamp.