Create a data lake structure using AWS Lake Formation or Amazon S3 and Amazon Redshift. For structured relational data, create an Amazon RDS instance within a VPC. For
compatible enterprise applications, use Amazon API Gateway and Lambda functions to create an interface into the RDS instance. For compatible databases, use AWS Database Migration Serviceto create copies or export structured data sets. For industrial IoT (IIoT) and automation equipment, use AWS IoT Core and Amazon Kinesis Data Firehoseto stream data into the Data Lake. For external or batch interfaces, use AWS Transfer for SFTPto put data into the Data Lake. Once data ingest paths are set up, use AWS Glueto build the data catalog and to create the ETL jobs for data processing. Use Amazon SageMakerto train and deploymachine learning models from the data sets. Use AWS AppSync to build a GraphQL endpoint with AWS Lambdaresolvers to provide an application interface to the data.
