Business Challenge: EDA and SQL

Introduction

A data project lifecycle has many phases, rather than being just an isolated analysis in a single tool. In this project you will experience doing an analysis using both Python and SQL to obtain the final result, by exploring each tool's behavior.

Project Overview

Pick up a dataset in our common datasets repos and break your work into big steps:

1. Pick a topic and choose a dataset on that topic. Build around 10 Business questions to answer about this topic.
   • Try to build the questions before knowing everything about the data
   • If not possible, do step 2. first
2. Data Analysis: Understand your dataset and create a report (word document) about it
3. Data Exploration and Business Understanding:
   • Import your dataset into SQL
   • Answer your Business questions with SQL Queries

Dataset repos

• Kaggle
• Machine Learning Repository
• PorData
• And many more

Bonus

• Bonus points if you augment your data with data your obtain through WebScrapping
• Bonus points if you include visualizations from Python and/or Tableau in the final presentation

Deliverables

1. Python Code: Provide well-documented Python code that conducts the analysis and SQL upload.
2. SQL text file (.sql) well commented document with all the queries answering the Business questions
3. Short Presentation: Structure the presentation in the following way:

• Intro Slides: introduce the problem and the datasets
• Data cleaning and assumptions
• Business questions and SQL query (1 slide per question with a print screen of the query and the answer is enough)

4. PDF Document with notes you might want to share