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This ‘need for speed’ drives a rethink on building a more modern datawarehouse solution, one that balances speed with platform cost management, performance, and reliability. In this way, the analyticapplications are able to turn the latest data into instant business insights. Schema Management.
On top of that, I had to make that data available to our custom-built application via a secure RESTful endpoint with a less than one second response time. I was amazed that I could do all of that without having to initially move and transform the data. From there, the data could be ingested by any standard reporting tool.
Disclaimer: Rockset is a real-time analytics database and one of the pieces in the modern real-time data stack So What is Real-Time Data (And Why Can’t the Modern Data Stack Handle It)? Every layer in the modern data stack was built for a batch-based world. The problem? Out-of-order event streams.
Step 5: Data Validation This is the last step involved in the process of data preparation. In this step, automated procedures are used for the data to verify its accuracy, consistency, and completeness. The prepared data is then stored in a datawarehouse or a similar repository.
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