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The Future of Big Data with Gen AI: Accelerating System Migration and Boosting Efficiency

Description

In the fast-evolving landscape of big data, frequent system migrations pose significant challenges, particularly in code conversion and adoption of new data processing engines. This presentation addresses the inefficiencies of manual code migration processes faced by big data teams, emphasizing the need for scalability and faster adoption rates. We propose an innovative approach that utilizes Gen AI and cloud services such as AWS Bedrock, Redshift, Glue, Athena, and S3, coupled with robust automated testing mechanisms. Our methodology has proven effective, demonstrating a 75% reduction in the time and effort required for code conversion and testing during migrations. We will also explore further applications of this strategy across the big data domain, highlighting its potential to significantly enhance operational efficiency for big data teams.

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