Tracking the changes in datasets is one of the core functionalities of any data warehouse. The most common form of historization is called slowly changing dimension type 2 (SCD2). Instead of simply overwriting changes in a dataset (which is a type 1 ...
Hello Jessica,linked dimensions in SAC are usually a performance killer. If possible, you should try to join your models in DSP as this is pushing the join into the database. Currently it is not possible to merge two analytic models, so you would hav...
Hi Avinash,if you want the business users to just be able to use the data builder objects in SAC, you should do the following:Provide the role "DW Consumer" to the business users. This ensures that the users can not log in to Datasphere but only see ...
Great blogpost and a great feature!
It's nice to see that already existing Analytical Datasets with this feature can be converted to an Analytic Model by simply mapping the input parameter to a new variable.
Can't wait for more advanced possibilite...
If you add your SAC tenant in the monitoring area of the datasphere catalog, you can see all the SAC Stories and their lineage to the underlying datasphere models.
Hi Asad,
thanks for your comment. Creating an SQL View with a conditional join could also be a solution to find the right dimensional data for every transaction. However, creating joins is not the recommended way of connecting dimensional data with ...
