An NFT marketplace with predictive and analytical modeling on the industry trends and growth to visualize and recommend creators and NFTs with uprising value potential

The popularity and recognition of blockchain technology along with dealing with crypto assets has grown multifariously in recent years. A direct consequence of this is also seen in the NFT marketplace mushrooming as witnessed in recent years. The aim of this paper is to implement ETL pipelines to transform data on the EVM nodes into a centralized database for analytical modelling. This research involves perform analytical modeling on NFT trades to understand and recommend potential uprising high-value NFTs to buyers. This paper encompasses concepts and procedures of extracting data from EVM nodes, transformation of raw data by identifying patterns in hex values, visualizing data using SparkSQL, analytical modeling based on statistics and integration with a cross-platform flutter application. As the end product, we aim to deliver a customized NFT marketplace packaged as a mobile app that allows analysis of various trends that can be filtered by category, creator, value, etc.