Capstone-Project-GP-2

Track 1: e-commerce business / marketing setting You’re a Data Analyst at an e-commerce company and the business requires a comprehensive analysis about the progress of their activity. In particular, they require a study about the progress of sales, inventory and products. The company data is stored in the following BigQuery database: bigquery-public-data.thelook_ecommerce. Your task is to query and extract the data, perform any cleaning if necessary, manipulate it, analyse it and create a compelling presentation of your results in Tableau, that you’ll deliver to the business. Your final output should provide insights about the following topics: Website activity: the events table contains session-level data about the user's online behaviour. Some examples: which parts of the website are the most visited? where is the traffic coming from? … Demographic composition: the users table includes customer information. Some examples: age / gender of your customers, popular countries / cities, customers that are particularly loyal (multiple purchases), … Product performance: the product table describes the product catalogue as well as costs and retail prices of each element, but it’s in the order-item table that you will be able to see how many times a certain product was sold. Some examples: best/worst sellers, which products bring the highest/lowest revenue, gender/age preferences for certain products / categories, … Inventory status: the inventory_items sheet shows stock availability and the distribution_centres table shows where each distribution centre is located. Some examples: are there availability issues for any product / category? is there a distribution centre that is problematic? … Other insights: don’t forget about the orders table, which provides order-level information on your customer’s transactions. Finally, as explained above, you will use the insights gained from your analysis above to prepare a presentation in the form of a dashboard, story or PowerPoint/Google Slides in which you’ll explain the context, the insights you found, their interpretation and any recommendations / next steps, explaining how they can be leveraged to improve the future of the business. As an added bonus, implement one of the following predictive analysis and try to fit them into your narrative: What-if analysis (eg: profit margin) Forecast (eg: sales) Linear regression (eg: predict age or gender given items purchased) Note: for this project, you should use all three of: SQL (grouping, joining data, etc), Python (cleaning, exploring, analysing) and Tableau (visualisation and presentation).