Data architecture for dataset

Question & Answer
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1

What are the best practices for designing and implementing the data architecture for datasets in Quicksight?
In terms of reusability, scalability, efficiency and management of datasets within Quicksight.

We are migrating to a new AWS account and want to get the first steps right.

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Hi @Raphael_Tan - Thanks for posting this question. Some of the great tips are available in the below link -

Also depending upon the use case and problem statement some of the tuning or best practices can be implemented.

@David_Wong @DylanM @duncan @Biswajit_1993 - Any advise from your side.

Regards - Sanjeeb

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Hello @Raphael_Tan, the blog post that @Sanjeeb2022 shared provides some great information for you to achieve scalable dashboard and dataset management in QuickSight.

I would also just highly recommend utilizing SPICE ingestion for datasets with incremental refreshes to achieve the best performance for your dashboards. Also, managing table joins from your datasource either in custom SQL or creating a view in the datasource that you can then query directly from QuickSight. That process maintains the best performance while also makes editing the dataset as easy as possible.

I’ll link some documentation below and also mark this response as the solution. Please let us know if you have any further questions on this, and we will be happy to assist you further.

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