Amazon QuickSight launches Dataset-as-a-Source
Amazon QuickSight announced Dataset-as-a-Source, a new feature that saves customers time and improves data governance. Dataset-as-a-Source allows users to create a new dataset using one or more existing datasets as input, and combine it with brand new data sources, such as other databases, CSV files, and apps like Twitter. Curators can create central datasets that Authors can reuse to create their own. Curators can control the definitions of business metrics in the central datasets, and Authors save time by getting a starting point to create new datasets themselves. If the dataset’s definition needs to be updated, Curators can make changes to the central datasets and dependent datasets get automatically updated. Dataset-as-a-Source can be used to combine datasets with Direct Query, SPICE, or a combination of the two. To learn more, visit here.
Amazon QuickSight announced Dataset-as-a-Source, a new feature that saves customers time and improves data governance. Dataset-as-a-Source allows users to create a new dataset using one or more existing datasets as input, and combine it with brand new data sources, such as other databases, CSV files, and apps like Twitter. Curators can create central datasets that Authors can reuse to create their own. Curators can control the definitions of business metrics in the central datasets, and Authors save time by getting a starting point to create new datasets themselves. If the dataset’s definition needs to be updated, Curators can make changes to the central datasets and dependent datasets get automatically updated. Dataset-as-a-Source can be used to combine datasets with Direct Query, SPICE, or a combination of the two. To learn more, visit here.
Currently, Authors are dependent on Curators to create complex datasets, and have to wait while Curators spend time building them. Additionally, each dataset has to be created from scratch (from the original data sources). As a result, dataset owners have to replicate relevant business metrics in each individual dataset. When the metric definition changes, it is inefficient to update datasets one at a time, and you run the risk of missing the update in one particular dataset or making a mistake in one.
Dataset-as-a-Source allows Curators to create central datasets and share these with Authors on their team. Authors can use these datasets as a starting point to create their own datasets. Curators can define business metrics in central datasets that Authors can use, without having to redo the work of recreating the field themselves. Furthermore, Authors benefit from all the join and filter work Curators did, and don't have to do it again. If Curators wish to make any changes to these centrally-defined fields, they can make modifications in one central dataset and the associated datasets get the updates automatically, saving time and preventing errors.
Dataset-as-a-Source is available in Amazon QuickSight Standard and Enterprise Editions in all QuickSight regions - US East (N. Virginia and Ohio), US West (Oregon), Canada, Sau Paulo, EU (Frankfurt, Ireland and London), Asia Pacific (Mumbai, Seoul, Singapore, Sydney and Tokyo), and US West (GovCloud). For further details, visit here. Currently, datasets using Row Level Security (RLS) or Column Level Security (CLS) cannot be used as a source for a new dataset; but this will be added in the near future. RLS and CLS can still be applied to the dependent datasets created from the source dataset.