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The info pipeline for this data engineering project has five levels - data ingestion, NiFi GetTwitter processor that gets actual-time tweets from Twitter and ingests them into a messaging queue. Selection takes place within the Kafka matter.
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Azure SQL Databases instance for persistent storage; to shop forecasts and historic distribution knowledge.
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The second stream is utilized to receive alarms based upon the analyzed details and induce Lambda. Lambda triggers an SNS notification to deliver a concept, and the information is saved in Aurora DB.
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