Introduction

Analysis On Beauty Industry #

Our goal is to bring more meaningful and multi-dimensional data to users on cosmetic brands and products so that both brands and end-consumers can make informed decisions

Data Collection: utilize different tools such as Tweepy API, XHR requests to extract product, twitter, brands, reviews and ingredient data from various sources

Data Cleaning: utilize Python and OpenRefine to clean data and make them ready to import into MySQL

Data Storage: database is stored in cloud (GCP) to allow multiple remote collaborators and MySQL Workbench was chosen as GUI tool

Data Model: EER and dimensional model created

Data Analysis: utilize SQL, Pandas, NLP libraries to perform analysis

Data Visualization On 5 Business Use Cases： Brand Perception Based On Sentiment Of Tweets Key Performance User Journey On Demo App Built On Tkinter Competitor Lookup Customer Demographic and Attribute Distribution