Why use Amazon Web Services for data storage? AWS provides big data services at a small cost, offering one of the most full-featured and scalable solution sets around. Start here to explore your storage and framework options when working with data services on the Amazon cloud. Your guide, Lynn Langit, a working big data architect, helps you navigate the options when it comes to file storage, relational and NoSQL data storage, data warehousing, graph and ledger databases, and data lakes. Plus, learn how to run open-source processing tools such as Hadoop and Spark on AWS and leverage new serverless data services, including Athena serverless queries and the auto-scaling version of the Aurora relational database service, Aurora Serverless.

Topics include:

Benefits of AWS
File storage with S3, Glacier, EBS, and EFS
Uploading files to AWS
Exploring AWS Relational Database Service (RDS)
Using the RDS Query Editor
Creating NoSQL databases with AWS DynamoDB
Creating data warehouses with AWS Redshift
Creating graph databases with AWS Neptune
Processing big data with Hadoop, Spark, and AWS EMR
Analyzing big data with Athena queries
Preparing and loading data for analytics with AWS Glue
Setting up a secure data lake with AWS Lake Formation

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