About the webinar:
ETL (Extract, Transform & Load) has been one of the daunting tasks on a big data platform such as Apache Hadoop, and Spark. Most of the time developers will write tons of code to build data pipelines and job control flow. AWS has brought Glue ETL tool which makes ETL easier and graphically very attractive. One of the great features of AWS Glue is 100% serverless and it does not require cluster provisioning and management. Behind the scenes, Glue uses the launch Apache Spark cluster to process the data in the ETL flow. Moreover, cost is also based on pay-per-use.
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Key Takeaways:
- Spend more time on data processing logic instead of writing job flow and data mapping
- Less headache of launching the EMR Spark cluster
- Better error handling and job control
- Log management using Cloudwatch
Who Should Attend:
- Chief Data Officer
- Director of Engineering
- Director of Analytics
- Data Architects, Systems Architects, and Cloud Architects
- Data Engineers
Speakers
Abhi Tripathi
Principal Solutions Architect – Big Data & Cloud, R Systems
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