This is a project/ case study for my google data analytics certificate But Here I will Focus on The First Part of The Project Which is Data Gathering and Processing Data from Dirty to Clean.
- Case Study Scenario.” You are a junior data analyst working in the marketing analyst team at Cyclitic, a bike-share company in Chicago. The director of marketing believes the company’s future success depends on maximizing the number of annual memberships. Therefore, your team wants to understand how casual riders and annual members use Cyclitic bikes differently. From these insights, your team will design a new marketing strategy to convert casual riders into annual members. But first, Cyclitic executives must approve your recommendations, so they must be backed up with compelling data insights and professional data visualizations. “
- This Data Contain 4 Separate Csv Files. The 4csv are divided into 4quarters of the year 2019.The Data Is from a bike-sharing company. Data Source Link: https://divvy-tripdata.s3.amazonaws.com/index.html
- The main Object is to understand how casual and annual members use Cyclitic bikes differently so that we can build a new marketing strategy that will convert casual riders into annual members.as a junior data analyst we have to come up with business recommendations to help our stakeholders achieve their goal. The Recommendation will be based on insights pulled from the company’s data.
- For as to help the company make data-driven decision we will need to analyze data and get insights from the data that best fit company’s main objective. But for us to do that we have to prepare and process data from dirty to clean to ensure that the data is clean, one of the reasons for cleaning data is to ensure that our insights are not bias. According to Harvard Business Review” Bad Data Costs the U.S. $3 Trillion Per Year”, source: https://hbr.org/2016/09/bad-data-costs-the-u-s-3-trillion-per-year , (imagine this is the us only). Therefore, we will first Prepare Our Data for analysis by cleaning it.