In a world where an ever-increasing amount of data is being gathered, companies often find themselves without the tools to optimally use the often unstructured data they’ve gathered. By trackit.io.
How can Company X manage to salvage the unstructured data it has gathered and still make use of it in a structured way? Solution: ETL pipeline — a pipeline that automatically Extracts data from their NoSQL database, Transforms it into a specific format suitable for exploitation and Loads it into a destination relational database.
The article then describes:
- AWS services that allow you to clone and migrate data
- Bridging the gap
- A DynamoDB to Aurora ETL pipeline architecture
- How the pipeline works
- Data propagation
- Lambda functions for Quality control
… and more. To get the schema of example ETL architecture and to learn pros and cons follow the link to the full article. Nice one!
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