AWS Big Data

AWS Big Data. Real-Time Analytics on Streaming Data with Amazon Kinesis and Amazon Elasticsearch Service

DESCRIPTION
Assist Facebook to do a continuous monitoring system to detect sentiment changes in a social media feed to respond to the sentiment in near real time.
Problem Statement:
Data streaming is used everywhere; from social networks like Facebook to mobile and web applications, IoT devices, instrumentation in data centers, and other sources. As the speed and volume of data increases, the need to perform data analysis in real time with machine learning algorithms and extract a deeper understanding from the data becomes even more important.
Domain: Sentiment Analysis of Social Media Platform
Analysis to be done: Collect and store streaming data, use Amazon Kinesis Analytics to process and analyze the streaming data, apply machine learning algorithm to detect anomalies in the system.
Steps to perform:
Create Kinesis delivery stream
Simulate streaming application to detect anomalies
Open Elasticsearch service and create a new domain
Configure Kinesis Firehose to export the results to Amazon ES
Update the buffer size and existing IAM role for the process
Open the Amazon Kinesis Analytics console and create a new application
Connect to the source for further analysis
Launch SQL_Editor and start the application
Load the processed data into Kinesis Firehose delivery stream
Visualize the data using Kibana

AWS Big Data

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