Working with Datasets
A dataset corresponds to a physical table or view in a data warehouse, or the results of a SELECT statement. The first step in designing an AtScale model is to import the physical tables or views that the model will be based on. (Later, you can create additional datasets that are based on the results of SELECT statements; these datasets are called query datasets.) To import a table or view as a dataset into an AtScale model definition, the AtScale organization in which your project and model are located must be connected to a data warehouse.
- Adding Datasets The first step in designing an AtScale model is to import the physical tables and views that the model will be based on.
- Removing Datasets from Projects and Models
- Viewing a Sample of Dataset Rows AtScale lets you to view a sample of a dataset's rows. Viewing a sample of rows allows you to examine the column values and decide which data to base your model attributes on.
- Adding Calculated Columns to Datasets for Simple Data Transformations Calculated columns are a way to add simple data transformations to a dataset. After a calculated column is added to a dataset, it can be used as the basis of a model attribute, just like any other dataset column.
- Searching for Columns in Datasets Datasets can contain a very large number of columns. If you a looking for one or more particular columns in a dataset on the Canvas, however, you can find them quickly by using one or more search criteria in the search field at the top of the dataset. Columns not matching the criteria are filtered out, so that the dataset lists only those that match.
- Editing the Dataset Type When you edit a dataset, you can change the underlying table or query that it is pointing to.