Cloud:
Version Control System:
Programming Language - PYTHON:
BIG DATA TOOL AND SOFTWARES:
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Project Introduction:
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The project aims to perform data analysis using Apache Hive on a telecom dataset to gain insights into customer behavior, churn, and related factors. Telecom companies often face challenges in retaining customers, making it essential to understand the data for informed decision-making.
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Problem Statement:
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The telecom dataset contains information about customers, their services, contracts, and churn status. The goal is to analyze this data to answer various questions and gain actionable insights, including but not limited to:
- Total number of customers in the dataset.
- Number of customers who have churned.
- Distribution of customers based on gender and SeniorCitizen status.
- Total charge due to churned customers.
- Churn analysis based on contract type, average monthly charges, tenure, payment methods, and more.
- Performance optimization with joins when integrating demographic data from another dataset.
- Advanced analysis, including the distribution of payment methods, churn rates for different InternetService categories, and more.
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Key Takeaways:
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At the end of this project, you will have gained valuable experience in using Apache Hive for data analysis, which can be applied to various business scenarios. Some key takeaways from this project include:
- Proficiency in data loading and exploration in Hive.
- Ability to perform intermediate and advanced data analysis tasks, such as partitioning and bucketing for better query performance.
- Understanding the performance implications of different types of joins.
- Advanced insights into customer behavior, helping the telecom company make data-driven decisions.
- The ability to identify patterns and factors contributing to churn, enabling proactive customer retention strategies.