The project aims to develop a real-time analysis system using Apache Kafka and Apache Spark. The system will collect real-time data and stream the data into Kafka. Apache Spark will then be used to process and analyze the data in real-time. The processed data will be visualized using appropriate visualizations and graphs.
The system will have two main components:
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Data Collection: This component will collect real-time data from various sources such as IOT, SCADA, CCTV, Stock Indexes, Weather Data ...etc. The data will be cleaned and transformed into a structured format before streaming it into Kafka.
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Data Processing and Visualization: This component will process the real-time data streams using Apache Spark. Spark will perform various real-time analysis tasks such as trend analysis, stock prediction, and outlier detection. The processed data will then be visualized using interactive dashboards and graphs to provide real-time insights into the stock market trends.
The system will be scalable, allowing it to handle a large volume of data streams and perform real-time analysis.
The project will be implemented using a combination of technologies such as Apache Kafka, Apache Spark, Docker , Jupyter Notebook, and a front-end visualization tool such as Grafana. The implementation will be based on a On-premises architecture, ensuring high availability and scalability of the system.
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