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https://github.com/szapp/magistdataanalysisvisualization

Case study: Data analysis and visualization to evaluate and recommend a business partnership. Team project for data-driven business with SQL and Tableau
https://github.com/szapp/magistdataanalysisvisualization

dashboard data-analysis data-science data-visualization data-viz sql tableau-public

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Case study: Data analysis and visualization to evaluate and recommend a business partnership. Team project for data-driven business with SQL and Tableau

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# Magist Data Analysis and Visualization



[![Tableau Public](https://img.shields.io/badge/tableau-dashboard-blue?logo=tableau&logoColor=white)](https://public.tableau.com/views/MagistAnalysis_17146788675680/Recommendation)



Case study: Data analysis and visualization to evaluate and recommend a business partnership. Team project for data-driven business with SQL and Tableau.



## Project



Eniac is a online marketplace specializing in Apple-compatible accessories. To enter the Brazilian market, Eniac is considering a partnership with Magist, a Brazilian company that offers a centralized order management system to connect small and medium-sized stores with the biggest Brazilian marketplaces.



To help Eniac make an educated decision, two questions are at the core of this project.



1. Is Magist a good partner for high-end tech products?

2. Is Magist's delivery service fast enough?



We found that Magist represents a small tech sector and provides delivery services subpar to Eniac's expectations. Based on the provided data, we therefore do not recommend Magist as a partner at this time.



[![Tableau visualization preview](TableauVisualizationPreview.png)](https://public.tableau.com/views/MagistAnalysis_17146788675680/Recommendation)



> [!TIP]

> Click on the preview to interact with the published Tableau dashboard



## Languages and libraries used



- SQL (with MySQL)

- Tableau Public



## Key learning



- Explore the undocumented relational database describing Magist's services

- Join and query the database tables to extract and filter relevant information about Magist's performance

- Agree on various approaches and divide the tasks among the team

- Clean the data and identify outliers

- Visualize the key findings using Tableau

- Research the Brazilian market and put the data into context

- Compile the insights across team members in a cohesive way to reach a conclusion

- Present the findings and make a recommendation for Eniac



## Challenges overcome



- Understanding the undocumented database

- Establishing a definition for high-tech products based on product categories

- Working with a data in a foreign language (specifically customer reviews in Portuguese)

- Identifying the strongest findings and stripping irrelevant insights

- Presenting the results in a concise manner to meet time restrictions



## Resources



### Analytics



- [Schema.pdf](Schema.pdf) - Schema of the relational database

- [Revenue.sql](Revenue.sql) - Query to extract the revenue information

- [Delivery.sql](Delivery.sql) - Query to extract the delivery times

- [Reviews.sql](Reviews.sql) - Query to extract the customer complaints



### Visualization



- [MagistAnalysis.twbx](MagistAnalysis.twbx) - Tableau Public Dashboard

- [Published Tableau Public Dashboard](https://public.tableau.com/views/MagistAnalysis_17146788675680/Recommendation)

- [Presentation.pdf](Presentation.pdf) - Project presentation including the final recommendation



Tableau Public Dashboard link  

https://public.tableau.com/views/MagistAnalysis_17146788675680/Recommendation