Streamlining Real-time Data Analysis and Building Scalable Solutions for Efficient Data Management and Insights Extraction for an Automobile Industry

Solutions

• Bike data is collected via AWS IoT Core and routed to Amazon MSK for processing.
• A dedicated AWS Lambda function converts compressed binary data into JSON format, which is then sent to various Kafka topics.
• Logstash plays a crucial role in preprocessing the JSON data from Kafka, flattening it, and incorporating calculated fields and flags as per client specifications.
• The processed data is seamlessly integrated with Amazon OpenSearch for real-time analysis and concurrently stored in Amazon S3 for archival and batch processing purposes.
• AWS Glue is utilized to automate the creation of tables for the data stored in Amazon S3, ensuring structured accessibility.
• Amazon Redshift serves as a robust data warehousing solution, facilitating multiple queries tailored to user requirements and incorporating data from Amazon DynamoDB for comprehensive insights.
• Aggregated and diverse table data are unloaded into Amazon S3 in Parquet format for optimized storage, while Amazon QuickSight leverages data from Amazon Redshift to generate intuitive and actionable dashboards for enhanced decision-making.