Adding dimensions

Understand dimensions in Drivetrain, including how to navigate, add, and manage them, to report and analyze your data effectively.

What is a Dimension

Dimensions are attributes of metrics by which you can view, break down and compare while performing analyses.

By default, all column names in your dataset are available to be added as dimensions to any metric created from it.

For example, in the NetSuite transactions dataset referred to in the previous section, every column name is a dimension and all 20 column names can be added as dimensions:

Transaction ID, Transaction Type, Transaction Date, Posting Date, Amount, Account Number, Account Type, Account Full Name, Account category, Account, Cashflow account, Cashflow expense category, Cashflow activities , Balancesheet category , Balancesheet Account , Balancesheet Account Category , Department, Department Group, Vendor Name, Memo

Dimension items (or Dimension values)

Each dimension contains a list of dimension items or values within it.

For example, the Department dimension in the above dataset contains values such as: Admin, Sales, Marketing, Customer Success, etc.

Navigating dimensions

The Dimensions page can be accessed from Settings by clicking on Dimensions.

Here you can see a list of all the dimensions added on the left pane. You can search for dimension names in the search bar.

Clicking on a dimension name displays the list of dimension items within it in the center pane.

Adding dimensions

There are three ways to add dimensions in Drivetrain:

1. From the Dimensions page

2. Via the Metric Builder
3. Via the Models page

Adding dimensions from the Dimensions page

• Click on the + icon next to List of Dimensions.

• In the New dimension modal window, enter the dataset's column name and select an option from the auto-suggest dropdown.

• The dimension items get automatically populated from dataset's column name. Only unique values from the column name are added as dimensions items.

Adding dimensions via the Metric Builder

When a metric is saved, all the dataset column names added to the Rows component in the Metric Builder page are automatically created as dimensions.

However, only a maximum of three dimensions can be created per metric in this manner since that's the maximum number allowed in Rows. You can manually add more dimensions to analyze the metric in a report by adding them from the Dimensions page.

Adding dimensions via the Models page

The Models page offers an automated way to add column names from datasets as Dimensions.

These dimensions will be available to all metrics created from that dataset for analysis and break down.

Follow the steps below to create dimensions in this manner:

• In the Models page, create a variable or select an existing variable.

• Hover the mouse over the variable, click on the kebab menu (⋮) and select Dimensions.

• In the Dimensions pop-up, select From columns and add the desired column names from the dataset(s).

Deleting a Dimension

• Select the dimension name to delete from the left pane.

• Click on the kebob menu (⋮) on the top right of the page.

• Click Delete dimension and click Delete in the warning modal.

FAQs

What happens when a dimension name is present in multiple datasets? What if datasets share a column name?

Datasets can have columns whose names are identical. In such cases, the dimension items will be a union of the unique values contained in the columns of both datasets.

For example, consider two datasets:

1. Customer Master (linked from Google Sheets)

2. Opportunities (linked from Salesforce)

Both datasets contain the Region column with different list of items.

If a new dimension with the name Region is created from the Dimensions page, it will contain the union of the unique items from both datasets as shown below:

Note: When drilling down on a metric, Drivetrain automatically lists only those dimensions from the dataset from which the metric was created.

Why is a dimension blank? It's not showing any values/items.

1. Check to see if the column in the dataset from which you created the dimension contains at least one value. If the column doesn't contain any values, (i.e. it's completely blank or missing), then the dimension will be empty.

2. There may exist multiple dimensions with same name across different datasets. Check to see if you're looking at the dimension from the desired dataset.

Which dimensions are available to drill down and analyze a metric?

All column names in your dataset are available to be added as dimensions to any metric created from it. You can slice and dice your metrics by any of the columns available in a dataset provided you add them as dimensions.