Which solution will meet these requirements with the LEAST operational overhead?
Store the data in an Amazon DynamoDB table. Create a proxy application layer to intercept and process the data that each application requests.
Store the data in an Amazon S3 bucket. Process and transform the data by using S3 Object Lambda before returning the data to the requesting application.
Process the data and store the transformed data in three separate Amazon S3 buckets so that each application has its own custom dataset. Point each application to its respective S3 bucket.
Process the data and store the transformed data in three separate Amazon DynamoDB tables so that each application has its own custom dataset. Point each application to its respective DynamoDB table.
Explanations:
Using a proxy application layer introduces additional complexity and operational overhead to manage data interception and transformation. This approach also requires maintaining the proxy layer, which could lead to potential performance bottlenecks and increased maintenance.
Storing data in an S3 bucket and using S3 Object Lambda allows for on-the-fly transformation of data. This means that the PII can be removed before the data is delivered to the applications that do not need it, thus minimizing operational overhead while efficiently managing data access and transformation.
While processing the data and storing it in three separate S3 buckets provides isolated datasets for each application, it creates redundancy and requires additional data management. Each bucket must be managed separately, increasing operational overhead and complexity in data processing and maintenance.
Similar to option C, processing the data and storing it in three separate DynamoDB tables increases complexity and operational overhead. Each table must be maintained, and the need to transform the data for each application results in redundant data processing efforts, which is inefficient compared to a more centralized approach.
It seems to me that the answer is:
Store the data in an Amazon S3 bucket. Process and transform the data by using S3 Object Lambda before returning the data to the requesting application.
I judge that the answer is:
Store the data in an Amazon S3 bucket. Process and transform the data by using S3 Object Lambda before returning the data to the requesting application.