bikesharing

Module 14

Overview of the analysis.

• Work with data visualization software called Tableau

• Create worksheets, dashboards, and stories to visualize key data from a New York Citi Bike dataset

Results:

1- The number of trips increase steadily at the beggining, than slowly decrease.

2- When comparing man and women there are differences. Number of trips for man increase stadily while for women have a more smother slope.

The unknown category shows no change.

3- 8 am in the morning and 5-7 pm are the peak hours.

Saturday has a different trend. Busier hours are 11 am to 5 pm.

4- Women and man show similar trends, however man have more trips. Peak hours are as mentioned in point 3 above.

5- Man subscribers are almost twice subscribers for women.

Thursday is the busiest day.

Summary:

1- Visualization helps data analytics setting a clear understanding of the information provided.

2- Tableau does a great job analyzing data and illustrating different graphs. This helps to analyze and showcase.

3- Bikesharing case is an excellent case for analyzing data with Tableau. The conclusions like, trips, hours, gender usage, times etc. can clearly be analyzed and visualized to inform the business decision of the business proposal.

Please visit the site to see the data in my Tableau https://public.tableau.com/profile/klaudio.kalari#!/vizhome/Module14_16012684627230/Dashboard1