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With online sales gaining popularity, tech companies are exploring ways to improve their sales by analyzing customer behavior and gaining insights about product trends. Furthermore, the websites make it easier for customers to find the products they require without much scavenging.
Preventing churn is key to improving revenue for Sparkify, a subscription-based company (fictitious). This project is to analyze data from Sparkify to build a model to predict user churn. First, a sample dataset (128MB) was used on a local machine to explore relevant features and develop a working model. Then similar steps were used to develop a…
The goal is to extract the data and gather insights from a real-life data set of an e-commerce company, using BIG Data tools like Hive, Hadoop, AWS etc.
In this project, we attempt to predict customer churn of a popular (not real) music service. We perform data analysis and machine learning model building on a large amount of data using Spark.
Criação de Esteiras de Deploy com Git Actions para subir uma infraestrutura na AWS com o Terraform fazendo controle da versão. Tecnologias utilizadas: escrita no formato Delta, Lambda Function, Kinesis Streaming, S3, Athena, Glue e EMR.