Column Actor Dataset

In Analytics, an actor is any entity in your business that is commonly used in analysis. User is the most common actor, but we have seen all kinds: Account, Subscription, Product, etc.

An actor is represented by a dataset - typically this maps to a dimension table in the data warehouse. However in some cases, there is no such dimension table in the warehouse, rather there is only an identifier column in an event table (i.e. Events.user_id). In this case, you can create a Column Actor dataset. The Column Actor dataset does not have any direct mapping to a warehouse table; it is defined solely by its relationship to the identifiers in other tables. However, Column Actors can still be used in all the ways a regular actor dataset can be used.

Create a Column Actor Dataset​

From the Datasets page​

Follow the steps below to create a column actor dataset:

1. On the left navigation panel, go to Data > Datasets.
2. On the Datasets page, click + New Dataset at the top and choose Column Actor Dataset.
3. Give your dataset a name, add a description(optional), and click Save.
4. The next step is to add Related Datasets - here, you can define a relationship with another dataset. You need to save your dataset before you can add related datasets. To add related datasets, follow the steps below.

1. 1. 1. Click + Add Related Dataset in the upper-right corner.
      2. Click the Dataset dropdown and choose the dataset you want to link to the current column actor dataset. As an example, let's select the Product Events dataset.
      3. Select the Cardinality for the relationship. The available options are:
         • many to one - Use this when multiple rows in the current dataset can match a single row in the related dataset based on the selected columns.
         • one to many - Use this when a single row in the current dataset can match multiple rows in the related dataset based on the selected columns. For the example, let's choose one to many.
      4. Now, define the relationship. Here, we only choose the value for the non-column actor because there are no physical columns in the column actor dataset. Here, we choose user_id - this means that the column actor dataset will use the user_id column of the Product Events dataset with no underlying physical table.
      5. Click Save.

5. Then, go to the Derived Columns tab where you can define new derived columns for this dataset. Learn more
6. In the Cohorts tab, you can define cohorts of rows of this dataset that represents logical groupings such as user cohorts. Learn more

Once the configuration is complete, you can view and access your dataset on the Datasets page.

Within Explorations​

You can also create new Column Actor datasets inline - that is, within the exploration templates. Wherever there is a requirement for actor selection within any exploration template, the inline column actor creation option will be available within the terminal selection. To create a new column actor dataset within an exploration,

1. On the left naviagtion panel, click + and choose an exploration template. As an example, let's choose Funnel.
2. After selecting a measure, you need to select the actor. Open the drop-down and click the Create Column Actor from an ID column option in the terminal select.
3. Provide a name for your dataset.
4. Select the related dataset and the columns.
5. Finally, choose the destination folder and click Save.

To edit your dataset,

1. On the left navigation panel, go to Data > Datasets.
2. On the Datasets page, click the dataset you want to edit.
3. Make necessary changes and click Save.

Duplicate your dataset​

To duplicate your dataset,

1. On the left navigation panel, go to Data > Datasets.
2. On the Datasets page, click the dataset you want to duplicate.
3. Click the three dots at the top-right and and click Save As. Give your copy a name and a description(optional), and choose a destination folder.
4. Click OK and the new dataset will be created.

Delete your dataset​

To delete your dataset,

1. On the left navigation panel, go to Data > Datasets.
2. On the Datasets page, click the dataset you want to delete.
3. Click the three dots at the top-right and and click Delete. A confirmation box will appear asking you to confirm the deletion - click Delete and your dataset will be deleted.