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A Data pipeline and a analytics dashboard that tracks the number of data updates in interval of 1 mins. The result is shown as a graph on the web browser. The input data is first supplied to Kafka, from which it gets streamlined to Spark streaming where some processing happens. Then the final data is updated on the browser.
As a Data Engineer for a fictional E-commerce startup, this project addresses the task of analyzing the web server logs to find the number of product pages visited and the number of items in the cart.
This project uses machine learning to categorize and prioritize airline user tweets based on content and sentiment. The goal is to reduce airlines' workload and provide personalized, empathetic responses to users. By training a sentiment analysis model, airlines can better understand customers' needs and improve their overall service on Twitter.
Statistics of coin’s volume in real time on Binance in the last 1 hour. Use Kafka to get data from Binance API, then Spark Streaming reads data stream.
This project will show an auto-updated map with the people interaction during COVID19 in the US using big data technologies to analysis a real-time stream of Twitter data.