Design to build an ETL process for Amazon Review datasets. Two datasets are chosen: Amazon Japan and Amazon Kitchenware. Analyze each dataset and determine if Amazon's vine program is trustworthy or not.

Used MapReduce, (NLP) in relation to big data, Google Colab, AWS , Visual Studio Code to Analyze Amazon Vine Reviews

Analyzed reviews for Music products on Amazon written by members of the paid, Amazon Vine program looking for potential bias in the reviews. PySpark was used to extract and transform the review data, which was connected to an Amazon Web Service RDS and loaded into pfAdmin.