Google Data Analytics: Capstone Project
Table of Contents:
About:
This repository contains the capstone projects developed during the final course of the Google Data Analytics Professional Certificate. Which is a specialization, with seven courses in total and a final project (the capstone), available through the Coursera platform.
The objective of this capstone project is to apply the knowledge developed during the course:
* Going through the Ask, Prepare, Process, Analyze, and Share phases of the data analysis process;
* Stating a business task clearly;
* Importing data from a real dataset;
* Documenting any data cleaning that you perform on the dataset;
* Analyzing the data;
* Creating data visualizations from your analysis;
* Summarizing key findings from your analysis;
* Documenting your conclusions and recommendations;
* Creating and publishing your case study.
For this, we're offered two tracks:
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Track 01: Working with existing questions and datasets.
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Track 02: Choosing your own questions and dataset.
It is not necessary to undertake any of the projects as there is no peer review to complete the course. However, it is highly recommended.
So, out of personal interest, and because I believe it will be of great value to my professional development, I will carry out the two projects offered in track 01, and also a personal project for track 02.
How this repository is structured:
Below we have two sections, one referring to Track 01 and the other referring to Track 02, where in the first we're offered a guided project with a set of data, problems, and results to be obtained already defined.
In the second, we have a slightly freer approach, where it is up to us to define the project we'll work on.
In each track I placed a link where the project was available, with the Jupyter notebooks in separate folders with each stage of the analysis process, and at the end a complete report documenting the results obtained.
Track 01 details:
"The first track involves a case study similar to what you might be asked for in a job interview. You will be given a business task, dataset, and list of specific deliverables that you must present to stakeholders. The first track will help you to create a case study that you could include in your portfolio to demonstrate job skills for future interviews. You can choose from between two cases. Once you decide which case study packet to use, you will read the details, complete the analysis, and create your finished case study."
"If this track interests you, explore the case study options and decide which one you want to perform. The case study packets available for download have everything that you need to complete your case study. Then, you will be ready to upload and share your case study with potential employers."
For details and specifics of the project, click on the link below
Scenario 01:
You are a junior data analyst working in the marketing analyst team at Cyclistic, 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 Cyclistic bikes differently. From these insights, your team will design a new marketing strategy to convert casual riders into annual members. But first, Cyclistic executives must approve your recommendations, so they must be backed up with compelling data insights and professional data visualizations.
Our goal is to answer three questions:
1. How do annual members and casual riders use Cyclistic bikes differently?
2. Why would casual riders buy Cyclistic annual memberships?
3. How can Cyclistic use digital media to influence casual riders to become members?
And create a report with a concise analysis and strong visualizations to deliver to executives.
Case Study 01
Scenario 02:
You are a junior data analyst working on the marketing analyst team at Bellabeat, a high-tech manufacturer of health-focused products for women. Bellabeat is a successful small company, but they have the potential to become a larger player in the global smart device market. Urška Sršen, cofounder and Chief Creative Officer of Bellabeat, believes that analyzing smart device fitness data could help unlock new growth opportunities for the company. You have been asked to focus on one of Bellabeat’s products and analyze smart device data to gain insight into how consumers are using their smart devices. The insights you discover will then help guide marketing strategy for the company. You will present your analysis to the Bellabeat executive team along with your high-level recommendations for Bellabeat’s marketing strategy.
Our goal is to answer three questions:
1. What are some trends in smart device usage?
2. How could these trends apply to Bellabeat customers?
3. How could these trends help influence Bellabeat marketing strategy?
Case Study 02
Track 02 details:
"The second track involves finding a public dataset that focuses on something that interests you. You could choose any topic about which you want to analyze data -- public bike use in your neighborhood, local wildlife migration, video game console sales, or anything else you are passionate about. You can follow the steps in the case study packet to guide you through this process. The case study packet provides public dataset recommendations, example business tasks, and steps to complete your analysis. This track is the most flexible, but that flexibility means that this track can be more challenging. You will have to use everything that you have learned so far to help you to complete this case study.
"If this track interests you, explore the case study packet to learn more details, find the public dataset that you want to use, and complete your analysis. Then, you will be ready to upload and share your completed case study."
For details and specifics of the project, click on the link below
Personal Case Study
Final considerations:
I had carried out this project for a long time, but I wasn't very confident with the results. Impostor syndrome didn't allow me to publish it...
But anyway, after a period of more in-depth study, I finally managed to deliver something a little more presentable, and well... better late than never.
I think this project is fundamental for the real learning of the content taught in the course, I believe it is more important than all seven courses together.
But in the end, that's what it's about. I thank Coursera and Google for allowing me to study such rich and high-quality content, and they are two entities that are having a very positive impact on my professional development!
