Building Data Analyst Agent
AWS AI Data Analyst: Query Your Data in Plain English!
To build an AI data analyst on AWS, structured data is uploaded to Amazon S3 as Parquet files. An AWS Lambda function instantly registers these schemas into the AWS Glue Data Catalog for fast querying. Simultaneously, a metadata JSON file is converted into semantic embedding vectors via Amazon Bedrock, allowing the AI to search datasets by conceptual meaning rather than just file names.
Secure access is managed via Amazon Cognito into a React app protected by AWS WAF and CloudFront. When a user asks a question, the Amazon Bedrock Agent locates the dataset, runs a dynamic SQL query via Amazon Athena, and passes the results to Claude Opus. The LLM then generates a plain English text summary and a visual Python chart for the user.
#aiagent #dataanalyst #AWS #ArtificialIntelligence #DataEngineering #AmazonBedrock #GenerativeAI #CloudArchitecture #Serverless #AmazonAthena #AWSGlue #ClaudeOpus #DevOps #TechTips #DataAnalytics #ReactJS
To build an AI data analyst on AWS, structured data is uploaded to Amazon S3 as Parquet files. An AWS Lambda function instantly registers these schemas into the AWS Glue Data Catalog for fast querying. Simultaneously, a metadata JSON file is converted into semantic embedding vectors via Amazon Bedrock, allowing the AI to search datasets by conceptual meaning rather than just file names.
Secure access is managed via Amazon Cognito into a React app protected by AWS WAF and CloudFront. When a user asks a question, the Amazon Bedrock Agent locates the dataset, runs a dynamic SQL query via Amazon Athena, and passes the results to Claude Opus. The LLM then generates a plain English text summary and a visual Python chart for the user.
#aiagent #dataanalyst #AWS #ArtificialIntelligence #DataEngineering #AmazonBedrock #GenerativeAI #CloudArchitecture #Serverless #AmazonAthena #AWSGlue #ClaudeOpus #DevOps #TechTips #DataAnalytics #ReactJS
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