Spotlight

info

🏗️ The Spotlight features are currently in beta. We're actively testing and improving them — some of the functionality might be subject to change.

Spotlight is a suite of features designed to put Metrics front and center. It simplifies data exploration, making it easy for business users to focus on metrics without dealing with complex tables or time dimensions.

Getting Started

Existing Lightdash users don’t need to do anything to get started! Spotlight features use your existing semantic layer and metrics definitions, so you can get started today.

Head to the ‘Metrics Catalog’ under the ‘Browse’ menu in the navigation bar.

Browsing the catalog

Browse all the project metrics you have access to (based on permissions and user-attributes) in the Metrics Catalog.

1. Search: Easily find metrics by their names or .yml descriptions using the searchbar.
2. View .yml descriptions: Click on any description to expand and view the full content, including rendered Markdown.
3. Categories: Use categories to streamline your metrics and KPIs. Filter metrics by category and add new ones directly in the UI. Users with editor permissions and above can click on any category cell to edit, rename, change its color, or delete it.
4. View popularity: Discover a metric’s popularity and see where it’s being used. Click to explore a complete list of charts which use the metric. Metrics are sorted by default to highlight the most used ones first.
5. Explore: Interactive viewers and above can dive deeper by clicking Explore to visualize the metric in a chart format.

Exploring a metric

Visualize your metrics in the Metrics Explorer.

1. Plot over time: View your selected metric plotted over a time dimension as a line chart. You can adjust this dimension or set a default time dimension in your .yml to simplify the process for users. See how
2. Filter by date: Use the date picker with convenient presets for quick selection. See how default presets work based on the granularity
3. Adjust the time granularity: Refine your view by choosing the desired level of date granularity.
4. Compare to:
   • 'This time last year': Compare the selected time period to the same period last year
   • 'Another metric': Compare to any other metric in the project that has a default time dimension specified in the .yml. This includes joins See how
5. Segment-by: Break down the metric by a dimension(that isn't a time, or a numeric dimension) in your dataset.

Configuring default time settings in .yml

We recommend setting up default time fields to make it easier for your business users and save them time.

To pre-select a time field in the explore view, simply define the default settings in your Lightdash .yml files.

Set a default time dimension on a table level in your Lightdash .yml file

1. Create or modify your table configuration in the .yml file. For example, to set a default time dimension on the events table:

version: 2
models:
  - name: events
    columns:
      - name: event_date
        description: "Event date"
        meta:
          dimension:
            label: "Event date"
            type: date
            time_intervals:
              - DAY
      - name: event
        description: "Event"
        meta:
          dimension:
            type: string
          metrics:
            count:
              type: count

2. Add the default time dimension at the table level:

version: 2
models:
  - name: events
    meta:
      default_time_dimension:
        field: event_date
        interval: DAY
    columns:...

3. Compile your project
4. Navigate to the metrics catalog
5. Open any metrics from the events table
6. All metrics with that default time set will be plotted against the event date with day granularity in the last 30 days

Set a default time dimension on a metric level in your Lightdash .yml file

This will override the time dimension defined on the table level.

1. Modify your existing table configuration to add a metric-level default time dimension:

version: 2
models:
  - name: events
    meta:
      default_time_dimension:
        field: event_date
        interval: DAY
    columns:
      - name: event
        description: "Event"
        meta:
          metrics:
            count:
              type: count
              # This will override the table level default time dimension
              default_time_dimension:
                field: event_date
                interval: MONTH

2. Compile your project
3. Navigate to the metrics catalog
4. Explore the Events' count metric
5. The metric will be plotted against the event date with month granularity, instead of the default day granularity applied to the table

FAQs

a. What time intervals are supported?

Currently, we only support: DAY, WEEK, MONTH, YEAR

b. What pre-filled filters are applied?

• Time grain Year -> current year to date
• Time grain Month -> past 3 months
• Time grain Week -> past 12 weeks
• Time grain Day -> past 30 days

So if one of your business users explores a metric with a default time grain of DAY, metrics will be shown for the past 30 days with granularity of days with the default time dimension prefilled.

c. Can I pull through other metadata from my .yml files?

Not yet, but soon you'll be able to manage metadata directly in the UI and sync it back to dbt.

Roles and permissions

Action	Project Admin	Project Developer	Project Editor	Project Interactive Viewer	Project Viewer
Browse the ‘Metrics catalog’	✅	✅	✅	✅	✅
Add/edit /delete ‘Categories’	✅	✅	✅	❌	❌
Open the ‘Metrics Explorer’	✅	✅	✅	✅	❌