Skip to main content

Dashboards

Dashboards are collections of dashboard elements. Dashboard elements are plots or tables created with a combination of measures and dimensions that can be joined together.

Dashboards are specified in YAML files, like all files in Zenlytic.

Dashboard Properties#

type: (Required) The type of the file. For these dashboard files is should always be dashboard.

name: (Required) The name of the dashboard. This name is used to uniquely determine the dashboard and presented in the url, so it must be unique across dashboards in your project. If you reference this dashboard elsewhere this is the name you will use. Like all names, it follows Zenlytic naming conventions

label: The label of the dashboard is what shows up to the end users of your data model. If not specified it defaults to the name of the dashboard.

description: This is the description of the dashboard. This is helpful to let business users know what plots and tables to expect.

filters: This is a list of filters which follow the field filter syntax.

  - field: orders.new_vs_repeat    value: New

elements: This is a list of dashboard elements, which are covered below.

Dashboard Elements

Dashboard elements determine what to display for each element in the dashboard.

Dashboard Element Properties#

model: (Required) The name of the model you want to base this dashboard element from.

metrics: (Required) This is a list of metric names to display in the dashboard element. For example, orders.total_revenue would reference the total_revenue measure in the orders view.

slice_by: This is a list of slices (dimensions or dimension_groups) to apply to the plot or table. For example, orders.new_vs_repeat references the new_vs_repeat dimension in the orders view, and orders.order_month references the dimension_group order using the month timeframe.

filters: This is a list of filters that follow the standard field filter syntax. For example, the following filter ensures that the product_name dimension in the order_lines view is not equal to "Handbag"

  - field: order_lines.product_name    value: -Handbag

cohort_by: This is a dimension group of type duration that you would like to cohort the plot by.

time_period: This is the time period for Zenlytic to apply to all metrics and slices in the query. The default value is any_time, which does not apply a time period filter. The options are: a datetime field filter. For more advanced, fine-grained controls over the time filters, use the field filters under the filters property.

sort: This is a list of sorts to apply. A sort is defined with a field (any field accessible in the data model) and value (either asc or desc, defaults to asc if empty) property like this:

sort:- field: orders.campaign  value: desc

Examples#

Here is an example of a dashboard file for a retention dashboard with two elements (the second of which is a cohort plot). The time period applied to both plots means that the data will all be within the last 30 days.

type: dashboardname: retention_dashboardlabel: Retention Dashboarddescription: Retention data broken out by various factors
elements:  - model: demo    metrics: [orders.repeat_order_rate, orders.average_order_value]    slice_by: [orders.product]    time_period: 30 days
  - model: demo    metrics: [orders.repeat_order_rate]    slice_by: [orders.product]    cohort_by: orders.weeks_duration_firstorder_thisorder    time_period: 30 days

Here is an example of a dashboard file with a filter at the dashboard level, and an additional filter applied to the second plot. The dashboard level filter will apply to both plots when the dashboard is run and/or when the filter is changed. The second of the two plots will have an additional filter applied which filters out the CabinSummerVideo_TikTok campaign from the results. This dashboard also includes a sort to make sure the campaigns are organized from highest in terms of total revenue to lowest.

type: dashboardname: sales_dashboardlabel: Sales Dashboard (with campaigns)description: Sales data broken out by campaign and repurchasing behaviorfilters:  - field: orders.acquisition_channel    value: -Organic
elements:  - model: demo    metric: orders.total_revenue    slice_by: [orders.new_vs_repeat, orders.product]    time_period: last_month
  - model: demo    metrics:      - orders.total_revenue      - orders.average_order_value      - orders.number_of_orders    slice_by: [orders.campaign]    time_period: last_month    filters:     - field: campaign       value: -CabinSummerVideo_TikTok    sort:    - field: orders.total_revenue      value: desc