Why Do You Need Data Transformation on S3

Apart from being one of the most-used cloud-based services in the world, AWS (Amazon Web Service) also offers a range of computing and storage services, one of the most popular being the Simple Storage Service (S3) of AWS. So, where does data transformation on S3 come into the picture?

Applications based in the cloud have specific requirements and often need a different view of the data in a dataset. For example, an e-commerce database needs personally identifiable information while the same dataset for a marketing campaign might have to be enriched with additional information about customer loyalty.

A newly-launched capability of AWS is the S3 Object Lambda that helps users in data transformation on S3 on the go where data stored in S3 buckets can be processed and transformed. It also works with existing applications and uses Lambda functions for automatic processing and data transformation on S3 as it is being retrieved from S3. Application code need not be changed as the Lambda function is invoked in line with a standard S3 GET request. 


Several use cases can be simplified with the data transformation on strategy.

·        Redacting personally identifiable information for analytics or non-production environments.

·        Adapting across data formats, such as converting XML to JSON.

·        Supplementing data with information from other services or databases.

·        Compressing or decompressing files as they are downloaded.

·        Resizing and watermarking images on the fly using caller-specific details, such as the user who requested the object.

·        Implementing custom authorization rules to access data.

This new data transformation on the S3 capability of AWS makes it easy to share and convert data across multiple applications.  

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