With just a few clicks, Stitch starts extracting your Amplitude data, structuring it in a way that's optimized for analysis, and inserting that data into your Amazon S3 data warehouse. Thankfully, products like Stitch were built to move data from Amplitude to Amazon S3 automatically. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time. This ETL (extract, transform, load) process is broken down step-by-step. This tutorial is intended for data owners who have data that resides in Amazon S3, and who want to process or migrate that data securely to Google Cloud. If all this sounds a bit overwhelming, don’t be alarmed. How to extract and interpret data from Responsys, prepare and load Responsys data into Amazon S3, and keep it up-to-date. This tutorial describes how to harden data transfers from Amazon Simple Storage Service (Amazon S3) to Cloud Storage using Storage Transfer Service with a VPC Service Controls perimeter. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Postgres, To Snowflake, To Azure Synapse Analytics, and To Panoply. Some folks choose to go with Amazon Redshift, Google BigQuery, PostgreSQL, Snowflake, Microsoft Azure Synapse Analytics, or Panoply, which are RDBMSes that use similar SQL syntax. S3 is great, but sometimes you want a more structured repository that can serve as a basis for BI reports and data analytics - in short, a data warehouse.
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