Dimensions reference

Dimensions are the columns in your table. They are the “attributes” of your data. For example, user_id in your users table is a dimension.

Dimensions usually match 1:1 with columns in your dbt models (see additional dimensions for counterexamples).

Adding dimensions to your project

Read more about adding dimensions to your project in our docs here.

For a dimension to appear in Lightdash, you just need to declare it in your dbt model’s YAML file.

models:
  - name: my_model
    columns:
      - name: user_id # will be "User id" in LightDash
        description: "Unique identifier for a user."

Dimension configuration

To customize the dimension, you can do it in your dbt model’s YAML file under the meta tag. The syntax depends on your dbt version.

If you want to declare multiple dimensions based on the same column, check additional dimensions section.

dbt v1.9 and earlier

models:
  - name: sales_stats
    meta:
      group_details:
        finance:
          label: Finance
          description: Finance-related fields.
      joins:
        - join: web_sessions
          sql_on: ${web_sessions.date} = ${sales_stats.date}
    columns:
      - name: revenue_gbp_total_est
        description: 'Total estimated revenue in GBP based on forecasting done by the finance team.'
        meta:
          dimension:
            type: number
            label: 'Total revenue' # this is the label you'll see in Lightdash
            description: 'My custom description' # you can override the description you'll see in Lightdash here
            sql: 'IF(${TABLE}.revenue_gbp_total_est = NULL, 0, ${registered_user_email})' # custom SQL applied to the column from dbt used to define the dimension
            hidden: false
            format: '[$£]#,##0.00' # GBP rounded to two decimal points
            groups: ['finance']
      - name: forecast_date
        description: 'Date of the forecasting.'
        meta:
          dimension:
            type: date
            time_intervals: ['DAY', 'WEEK', 'MONTH', 'QUARTER'] # not required: the default time intervals for dates are `['DAY', 'WEEK', 'MONTH', 'YEAR']`
            urls:
              - label: 'Open in forecasting tool'
                url: 'https://finance.com/forceasts/weeks/${ value.raw }'
              - label: Open in Google Calendar
                url: 'https://calendar.google.com/calendar/u/0/r/day/${ value.formatted |split: "-" |join: "/"}'
            required_attributes:
              is_admin: 'true'

dbt v1.10+ and Fusion

models:
  - name: sales_stats
    config:
      meta:
        group_details:
          finance:
            label: Finance
            description: Finance-related fields.
        joins:
          - join: web_sessions
            sql_on: ${web_sessions.date} = ${sales_stats.date}
    columns:
      - name: revenue_gbp_total_est
        description: 'Total estimated revenue in GBP based on forecasting done by the finance team.'
        config:
          meta:
            dimension:
              type: number
              label: 'Total revenue' # this is the label you'll see in Lightdash
              description: 'My custom description' # you can override the description you'll see in Lightdash here
              sql: 'IF(${TABLE}.revenue_gbp_total_est = NULL, 0, ${registered_user_email})' # custom SQL applied to the column from dbt used to define the dimension
              hidden: false
              format: '[$£]#,##0.00' # GBP rounded to two decimal points
              groups: ['finance']
      - name: forecast_date
        description: 'Date of the forecasting.'
        config:
          meta:
            dimension:
              type: date
              time_intervals: ['DAY', 'WEEK', 'MONTH', 'QUARTER'] # not required: the default time intervals for dates are `['DAY', 'WEEK', 'MONTH', 'YEAR']`
              urls:
                - label: 'Open in forecasting tool'
                  url: 'https://finance.com/forceasts/weeks/${ value.raw }'
                - label: Open in Google Calendar
                  url: 'https://calendar.google.com/calendar/u/0/r/day/${ value.formatted |split: "-" |join: "/"}'
              required_attributes:
                is_admin: 'true'

Lightdash YAML

type: model
name: sales_stats

group_details:
  finance:
    label: Finance
    description: Finance-related fields.

joins:
  - join: web_sessions
    sql_on: ${web_sessions.date} = ${sales_stats.date}

dimensions:
  - name: revenue_gbp_total_est
    description: 'Total estimated revenue in GBP based on forecasting done by the finance team.'
    type: number
    label: 'Total revenue' # this is the label you'll see in Lightdash
    sql: 'IF(${TABLE}.revenue_gbp_total_est = NULL, 0, ${registered_user_email})' # custom SQL applied to the column from dbt used to define the dimension
    hidden: false
    format: '[$£]#,##0.00' # GBP rounded to two decimal points
    groups: ['finance']
  - name: forecast_date
    description: 'Date of the forecasting.'
    type: date
    time_intervals: ['DAY', 'WEEK', 'MONTH', 'QUARTER'] # not required: the default time intervals for dates are `['DAY', 'WEEK', 'MONTH', 'YEAR']`
    urls:
      - label: 'Open in forecasting tool'
        url: 'https://finance.com/forceasts/weeks/${ value.raw }'
      - label: Open in Google Calendar
        url: 'https://calendar.google.com/calendar/u/0/r/day/${ value.formatted |split: "-" |join: "/"}'
    required_attributes:
      is_admin: 'true'

The table below shows all the dimension properties you can customize:

Property	Required	Value	Description
label	No	string	Custom label. If you set this property, this is what you’ll see in Lightdash instead of the dimension name.
type	No	Dimension type	The dimension type is automatically pulled from your table schemas in Lightdash but you can override the type using this property.
description	No	string	Description of the dimension in Lightdash. You can use this to override the description you have for the dimension in dbt.
sql	No	string	Custom SQL applied to the column used to define the dimension.
time_intervals	No	’default’ or OFF or an array[] containing elements of date, numeric, string options, or custom granularity names	’default’ (or not setting the time_intervals property) will be converted into [‘DAY’, ‘WEEK’, ‘MONTH’, ‘QUARTER’, ‘YEAR’] for dates and [‘RAW’, ‘DAY’, ‘WEEK’, ‘MONTH’, ‘QUARTER’, ‘YEAR’] for timestamps; if you want no time intervals set ‘OFF’. You can also include custom granularity names defined in lightdash.config.yml.
hidden	No	boolean	If set to true, the dimension is hidden from Lightdash. By default, this is set to false if you don’t include this property. Hidden dimensions are also excluded from drilldowns (View underlying data).
compact	No	string	This option will compact the number value (e.g. 1,500 to 1.50K). Currently supports one of the following: [‘thousands’, ‘millions’, ‘billions’, ‘trillions’, ‘kilobytes’, ‘megabytes’, ‘gigabytes’, ‘terabytes’, ‘petabytes’, ‘kibibytes’, ‘mebibytes’, ‘gibibytes’, ‘tebibytes’, ‘pebibytes’]
format	No	string	This option will format the output value on the results table and CSV export. Supports spreadsheet-style formatting (e.g. #,##0.00). Use this website to help build your custom format.
groups	No	string or string[]	If you set this property, the dimension will be grouped in the sidebar with other dimensions with the same group label.
urls	No	Array of url, label	Adding urls to a dimension allows your users to click dimension values in the UI and take actions, like opening an external tool with a url, or open at a website. You can use liquid templates to customise the link based on the value of the dimension.
richText	No	string	Rich text template for displaying formatted content in table cells. Supports Markdown, HTML, and LiquidJS templating.
required_attributes	No	Object with user_attribute, value	Limits access to users with those attributes (AND logic - all must match)
any_attributes	No	Object with user_attribute, value	Limits access to users with those attributes (OR logic - at least one must match)
colors	No	Object with value, color	Color for the values in the chart
image	No	Object with url	[WIP] Display images in table cells using URL templates. Supports LiquidJS templating for dynamic URLs.
case_sensitive	No	boolean	If set to false, string filters on this dimension will be case insensitive. Defaults to true. Overrides explore-level setting.

Type

The types of your dimensions are pulled from your data warehouse, automatically. You can override these types using the type meta tag in your .yml file. If you run lightdash generate to generate your .yml files, then Lightdash will add the type from your data warehouse to your .yml files automatically.

dbt v1.9 and earlier

- name: user_created_date
  meta:
    dimension:
      type: date

dbt v1.10+ and Fusion

- name: user_created_date
  config:
    meta:
      dimension:
        type: date

Lightdash YAML

dimensions:
  - name: user_created_date
    type: date

We currently support these dimension types:

Dimension Types
string
number
timestamp
date
boolean

Description

Column descriptions in your YAML file are automatically pulled into Lightdash and you can spot them if you hover over the dimension name.

Descriptions support any formatting that works with YAML, but the three characters used most often are:

Quotes for escaping

When you surround text with double or single quotes it will escape the text between so that any special characters recognized by YAML will still pass through to the Lightdash UI.

description: 'The contents of this column include this & that.'

Greater than symbol for folded text blocks

When you use >- it allows you to type descriptions that are multiple lines long in the YAML file, but the text will be combined into a single line when parsed. The lightdash generate command will automatically add this to keep YAML files easy to read.

This description in YAML:

- name: product_tier
  description: >-
    This is a longer description...
    ...that requires multiple lines
    and it will be combined in the Lightdash UI

Will appear like this in the Lightdash UI:

This is a longer description......that requires multiple lines and it will be combined in the Lightdash UI

Vertical bar for preserving line breaks

If you need line breaks to stay in place when they show up in the Lightdash UI, you can use a | character like this:

- name: product_tier
  description: |
    This is a longer description...
    ...that requires multiple lines
    and it will stay on multiple lines

And in Lightdash UI it will appear like this:

This is a longer description...
...that requires multiple lines
and it will stay on multiple lines

Using dbt doc blocks

You can also use dbt docs blocks in descriptions, more on that here.

Format

You can use the format parameter to have your dimensions show in a particular format in Lightdash. Lightdash supports spreadsheet-style format expressions for all dimension types.

To help you build your format expression, we recommend using https://customformats.com/.

dbt v1.9 and earlier

- name: us_revenue
  meta:
    dimension:
      type: number
      description: 'Revenue in USD, with two decimal places, compacted to thousands'
      format: '$#,##0.00," K"' # 505,430 will appear as '$505.43 K'
    additional_dimensions:
      percent_of_global_revenue:
        type: number
        description: 'Percent of total global revenue coming from US revenue.'
        sql: ${us_revenue} / ${global_revenue}
        format: '0.00%' # 0.67895243 will appear as '67.89%

dbt v1.10+ and Fusion

- name: us_revenue
  config:
    meta:
      dimension:
        type: number
        description: 'Revenue in USD, with two decimal places, compacted to thousands'
        format: '$#,##0.00," K"' # 505,430 will appear as '$505.43 K'
      additional_dimensions:
        percent_of_global_revenue:
          type: number
          description: 'Percent of total global revenue coming from US revenue.'
          sql: ${us_revenue} / ${global_revenue}
          format: '0.00%' # 0.67895243 will appear as '67.89%

Lightdash YAML

dimensions:
  - name: us_revenue
    type: number
    description: 'Revenue in USD, with two decimal places, compacted to thousands'
    format: '$#,##0.00," K"' # 505,430 will appear as '$505.43 K'
  - name: percent_of_global_revenue
    type: number
    description: 'Percent of total global revenue coming from US revenue.'
    sql: ${us_revenue} / ${global_revenue}
    format: '0.00%' # 0.67895243 will appear as '67.89%

Example format expressions:

Description	Format Expression	Raw Value	Formatted Output
Adds “km” suffix to the value	#,##0.00" km"	100000.00	100,000.00 km
		15000.25	15,000.25 km
		500	500.00 km
Format date with 12-hour clock	m/d/yyyy h:mm AM/PM	2023-09-05T15:45:00Z	9/5/2023 3:45 PM
		2024-01-20T08:30:00Z	1/20/2024 8:30 AM
Display the full name of the day	dddd	2023-09-05T15:45:00Z	Tuesday
		2024-01-20T08:30:00Z	Saturday
Format positive, negative, and zero values	"⬆️ "0;"⬇️ "0;0	-500	⬇️ 500
		200	⬆️ 200
		0	0
Text formatting	"Delivered in "@	2 weeks	Delivered in 2 weeks
		18 hours	Delivered in 18 hours
Percentage formatting	#,##0.00%	0.6758	67.58%
		0.1	10.00%
		0.002	0.20%
No formatting	0	12345232	12345232
		56.7856	57
Currency formatting	[$$]#,##0.00	15430.75436	$15,430.75
		15430.75436	$15,430.75
Compact currency in thousands	[$$]#,##0,"K"	15430.75436	$15K
		15430.75436	$15.43K
Compact currency in millions	[$$]#,##0.00,,"M"	13334567	$13.33M
		120000000	$120.00M

(Legacy) format and round options

Spreadsheet-style format expressions are the recommended way of adding formatting to your metrics in Lightdash. There are legacy formatting options, listed below, which are less flexible than the spreadsheet-style formatting.

If you use both legacy and spreadsheet-style formatting options for a single dimension, Lightdash will ignore the legacy format and round options and only apply the spreadsheet-style formatting expression.

Format (legacy)

dbt v1.9 and earlier

models:
  - name: sales_stats
    columns:
      - name: revenue
        description: 'Total estimated revenue in GBP based on forecasting done by the finance team.'
        meta:
          dimension:
            format: 'gbp'

dbt v1.10+ and Fusion

models:
  - name: sales_stats
    columns:
      - name: revenue
        description: 'Total estimated revenue in GBP based on forecasting done by the finance team.'
        config:
          meta:
            dimension:
              format: 'gbp'

Lightdash YAML

type: model
name: sales_stats

dimensions:
  - name: revenue
    description: 'Total estimated revenue in GBP based on forecasting done by the finance team.'
    format: 'gbp'

These are the options:

Option	Equivalent format expression	Description	Raw value	Displayed value
km	’#,##0.00” km“‘	Adds the suffix km to your value	10	10 km
mi	’#,##0.00” mi“‘	Adds the suffix mile to your value	10	10 mi
usd	’[$$]#,##0.00’	Adds the $ symbol to your number value	10	$10.00
gbp	’[$£]#,##0.00’	Adds the £ symbol to your number value	10	£10.00
eur	’[$€]#,##0.00’	Adds the € symbol to your number value	10	€10.00
jpy	’[$¥]#,##0.00’	Adds the ¥ symbol to your number value	10	¥10
percent	’#,##0.00%‘	Adds the % symbol and multiplies your value by 100	0.1	%10
id	’0’	Removes commas and spaces from number or string types so that they appear like IDs.	12389572	12389572

Round (legacy)

You can round values to appear with a certain number of decimal points.

dbt v1.9 and earlier

models:
  - name: sales
    columns:
      - name: revenue
        meta:
          dimension:
            round: 0 # equivalent format expression: '#,##0.0'

dbt v1.10+ and Fusion

models:
  - name: sales
    columns:
      - name: revenue
        config:
          meta:
            dimension:
              round: 0 # equivalent format expression: '#,##0.0'

Lightdash YAML

type: model
name: sales

dimensions:
  - name: revenue
    round: 0 # equivalent format expression: '#,##0.0'

Compact

You can compact values in your YAML. For example, if I wanted all of my revenue values to be shown in thousands (e.g. 1,500 appears as 1.50K), then I would write something like this in my .yml:

dbt v1.9 and earlier

models:
  - name: sales
    columns:
      - name: revenue
        meta:
          dimension:
            compact: thousands # You can also use 'K'

dbt v1.10+ and Fusion

models:
  - name: sales
    columns:
      - name: revenue
        config:
          meta:
            dimension:
              compact: thousands # You can also use 'K'

Lightdash YAML

type: model
name: sales

dimensions:
  - name: revenue
    compact: thousands # You can also use 'K'

Value	Alias	Equivalent format expression	Example output
thousands	”K” and “thousand”	’#,##0,” K”’ or ’#,##0.00,” K“‘	1K
millions	”M” and “million”	’#,##0,,” M”’ or ’#,##0.00,,” M“‘	1M
billions	”B” and “billion”	’#,##0,,,” B”’ or ’#,##0.00,,,” B“‘	1B
trillions	”T” and “trillion”	’#,##0,,,,” T”’ or ’#,##0.00,,,,” T“‘	1T
kilobytes	”KB” and “kilobyte”		1KB
megabytes	”MB” and “megabyte”		1MB
gigabytes	”GB” and “gigabyte”		1GB
terabytes	”TB” and “terabyte”		1TB
petabytes	”PB” and “petabyte”		1PB
kibibytes	”KiB” and “kibibyte”		1KiB
mebibytes	”MiB” and “mebibyte”		1MiB
gibibytes	”GiB” and “gibibyte”		1GiB
tebibytes	”TiB” and “tebibyte”		1TiB
pebibytes	”PiB” and “pebibyte”		1PiB

Time intervals

Lightdash automatically adds intervals for dimensions that are timestamps or dates, so you don’t have to!

For example, here we have the timestamp dimension created defined in our dbt project:

- name: created
  description: 'Timestamp when the user was created.'

Lightdash breaks this out into the default intervals automatically. So, this is how created appears in our Lightdash project:

Formatting added to a date or timestamp dimension will be applied to all of the time intervals for that dimension.

If you want to apply different formats for different time intervals, we recommend creating additional dimensions for time intervals where you want to customize the format.

Default time intervals

The default time intervals that Lightdash adds are…

For date type:

['DAY', 'WEEK', 'MONTH', 'QUARTER', 'YEAR']

For timestamp type:

['RAW', 'DAY', 'WEEK', 'MONTH', 'QUARTER', 'YEAR']

Disable time intervals

If you want to turn off time intervals for a dimension, you set the time_intervals property to OFF.

In this example, created would now appear as a single, timestamp dimension without a drop-down list of time intervals in Lightdash:

dbt v1.9 and earlier

- name: created
  description: 'Timestamp when the user was created.'
  meta:
    dimension:
      type: timestamp
      time_intervals: OFF

dbt v1.10+ and Fusion

- name: created
  description: 'Timestamp when the user was created.'
  config:
    meta:
      dimension:
        type: timestamp
        time_intervals: OFF

Lightdash YAML

dimensions:
  - name: created
    description: 'Timestamp when the user was created.'
    type: timestamp
    time_intervals: OFF

To customize the time intervals for a dimension, you can use the time_intervals parameter.

If you specify time intervals manually, then this overrides the default time intervals used by Lightdash.

dbt v1.9 and earlier

- name: created
  description: 'Timestamp when the user was created.'
  meta:
    dimension:
      time_intervals: ['DAY', 'DAY_OF_MONTH_NUM', 'MONTH', 'QUARTER_NAME', 'YEAR']

dbt v1.10+ and Fusion

- name: created
  description: 'Timestamp when the user was created.'
  config:
    meta:
      dimension:
        time_intervals: ['DAY', 'DAY_OF_MONTH_NUM', 'MONTH', 'QUARTER_NAME', 'YEAR']

Lightdash YAML

dimensions:
  - name: created
    description: 'Timestamp when the user was created.'
    time_intervals: ['DAY', 'DAY_OF_MONTH_NUM', 'MONTH', 'QUARTER_NAME', 'YEAR']

You can see all of the standard interval options for date and timestamp fields below. You can also add custom intervals using additional dimensions, there’s an example below the following tables.

Date options

Option	Description	Type	Displayed value	Notes
RAW	Original value	Date / DateTime	2019-01-01 / 2019-01-01, 09:30:30:300 UTC
YEAR	Date truncated to the nearest year	Date	2019
QUARTER	Date truncated to the nearest quarter	Date	2019-Q1
MONTH	Date truncated to the nearest month	Date	2019-01-01
WEEK	Date truncated to the nearest week	Date	2019-01-01	The start of the week depends on your warehouse configuration
DAY	Date truncated to the nearest day	Date	2019-01-01
HOUR	Datetime truncated to the nearest hour	DateTime	2019-01-01, 09 UTC
MINUTE	Datetime truncated to the nearest minute	DateTime	2019-01-01, 09:30 UTC
SECOND	Datetime truncated to the nearest second	DateTime	2019-01-01, 09:30:30 UTC
MILLISECOND	Datetime truncated to the nearest millisecond	DateTime	2019-01-01, 09:30:30:300 UTC

Numeric options

Option	Description	Type	Displayed value	Notes
DAY_OF_WEEK_INDEX	Index of the day of the week	Number	0	The value range and start of the week depends on your warehouse configuration
DAY_OF_MONTH_NUM	Day of the month	Number	21
DAY_OF_YEAR_NUM	Day of the year	Number	127
WEEK_NUM	Week number	Number	37
MONTH_NUM	Month number	Number	7
QUARTER_NUM	Quarter number	Number	3
YEAR_NUM	Year number	Number	2019
MINUTE_OF_HOUR_NUM	Minute number	Number	50
HOUR_OF_DAY_NUM	Hour number	Number	22

String options

Option	Description	Type	Displayed value
DAY_OF_WEEK_NAME	Day of the week	String	Monday
MONTH_NAME	Month name	String	March
QUARTER_NAME	Quarter name	String	Q3

Using custom granularities

Availability: Custom granularities are an Early Access feature.

You can define reusable custom time granularities in your lightdash.config.yml file and reference them in the time_intervals array. Unlike custom time intervals using additional dimensions, custom granularities appear in the date zoom dropdown alongside standard options (Day, Week, Month, etc.).

Step 1: Define custom granularities in lightdash.config.yml:

# lightdash.config.yml
custom_granularities:
  fiscal_quarter:
    label: "Fiscal Quarter"
    sql: "DATE_TRUNC('quarter', ${COLUMN} + INTERVAL '1 month')"
  week_monday:
    label: "Week (Mon-Sun)"
    sql: "DATE_TRUNC('week', ${COLUMN})"

Step 2: Reference them in your dimension’s time_intervals:

dbt v1.9 and earlier

- name: order_date
  description: 'Date the order was placed'
  meta:
    dimension:
      type: date
      time_intervals: ['DAY', 'WEEK', 'fiscal_quarter', 'YEAR']

dbt v1.10+ and Fusion

- name: order_date
  description: 'Date the order was placed'
  config:
    meta:
      dimension:
        type: date
        time_intervals: ['DAY', 'WEEK', 'fiscal_quarter', 'YEAR']

Lightdash YAML

dimensions:
  - name: order_date
    description: 'Date the order was placed'
    type: date
    time_intervals: ['DAY', 'WEEK', 'fiscal_quarter', 'YEAR']

The ${COLUMN} placeholder in the SQL expression is automatically replaced with the dimension’s column SQL at runtime. Custom granularities also inherit requiredAttributes and anyAttributes from the parent dimension.

See lightdash.config.yml reference for the full configuration options for custom granularities.

Custom time intervals with additional dimensions

You can also create custom time-based dimensions by using additional dimensions and groups. This approach groups custom dimensions with their parent date dimension in the sidebar, but these dimensions do not appear in the date zoom dropdown - they are only available as separate fields in the dimension list.

If you need custom time intervals to appear in the date zoom dropdown, use custom granularities defined in lightdash.config.yml instead.

Here’s an example of how that might look if you wanted to add year_of_week_iso grouped with the delivery_date dimension. Note that by defining the groups: option, we ensure that the new “Year of week” option is displayed grouped with the parent dimension in the sidebar.

dbt v1.9 and earlier

- name: delivery_date
  meta:
    dimension:
      label: "Delivery Date"
      type: date
      time_intervals: [ ... ]
    additional_dimensions:
      year_of_week_num:
        type: number
        label: "Year of week"
        sql: "yearofweekiso(${delivery_date})"
        groups: ["Delivery Date"]

dbt v1.10+ and Fusion

- name: delivery_date
  config:
    meta:
      dimension:
        label: "Delivery Date"
        type: date
        time_intervals: [ ... ]
      additional_dimensions:
        year_of_week_num:
          type: number
          label: "Year of week"
          sql: "yearofweekiso(${delivery_date})"
          groups: ["Delivery Date"]

Lightdash YAML

dimensions:
  - name: delivery_date
    label: "Delivery Date"
    type: date
    time_intervals: [ ... ]
  - name: year_of_week_num
    type: number
    label: "Year of week"
    sql: "yearofweekiso(${delivery_date})"
    groups: ["Delivery Date"]

Reference time intervals in other dimensions

You can reference specific time intervals of a dimension in other dimensions. When you define time intervals for a dimension (like session_start), Lightdash creates separate dimensions for each interval (e.g., session_start_day, session_start_month). You can reference these in custom SQL for other dimensions.

For example, if you have a user_created_at dimension with time intervals defined, you can calculate the duration between two dates using the DAY interval:

  - name: user_created_at
    meta:
      dimension:
        type: timestamp
        time_intervals:
        - DAY_OF_WEEK_NAME
        - WEEK
        - MONTH
        - RAW
        - DAY
        - HOUR_OF_DAY_NUM
        - QUARTER
  - name: first_purchase_at
    meta:
      dimension:
        type: timestamp
        time_intervals:
        - DAY
        - MONTH
        - QUARTER
  - name: duration
    meta:
      dimension:
        type: number
        sql: EXTRACT(DAY FROM ${first_purchase_at_day} - ${user_created_at_day})

In this example, ${user_created_at_day} and ${first_purchase_at_day} reference the DAY time interval versions of the user_created_at and first_purchase_at dimensions.

Groups

You can group your dimensions and metrics in the sidebar using the groups parameter.

To do this, you need to set up group_details in the model’s configuration. Then, you can use these groups to organize metrics and dimensions. You can create nested groups up to 3 levels.

dbt v1.9 and earlier

models:
  - name: baskets
    meta:
      group_details:
        product_details:
          label: Product Details
          description: 'Fields that have information about the products in the basket.'
        item_details:
          label: Item Details
          description: 'Fields that have information about the items in the basket.'

    columns:
      - name: basket_item_id
        description: 'ID for the product item within the basket.'
        meta:
          dimension:
            groups: ['product_details', 'item_details'] # this would add the dimension to a nested group: `product details` --> `item details`
      - name: product_name
        description: 'Full name of the product.'
        meta:
          dimension:
            label: 'Product name'
            groups: ['product_details'] # this would add the dimension under the group label: `product_details`

dbt v1.10+ and Fusion

models:
  - name: baskets
    config:
      meta:
        group_details:
          product_details:
            label: Product Details
            description: 'Fields that have information about the products in the basket.'
          item_details:
            label: Item Details
            description: 'Fields that have information about the items in the basket.'

    columns:
      - name: basket_item_id
        description: 'ID for the product item within the basket.'
        config:
          meta:
            dimension:
              groups: ['product_details', 'item_details'] # this would add the dimension to a nested group: `product details` --> `item details`
      - name: product_name
        description: 'Full name of the product.'
        config:
          meta:
            dimension:
              label: 'Product name'
              groups: ['product_details'] # this would add the dimension under the group label: `product_details`

Lightdash YAML

type: model
name: baskets

group_details:
  product_details:
    label: Product Details
    description: 'Fields that have information about the products in the basket.'
  item_details:
    label: Item Details
    description: 'Fields that have information about the items in the basket.'

dimensions:
  - name: basket_item_id
    description: 'ID for the product item within the basket.'
    groups: ['product_details', 'item_details'] # this would add the dimension to a nested group: `product details` --> `item details`
  - name: product_name
    description: 'Full name of the product.'
    label: 'Product name'
    groups: ['product_details'] # this would add the dimension under the group label: `product_details`

This example would look like this in the sidebar:

URLs

Lightdash users can interact with dimension values by clicking on them. If you’re already storing URLs in your models, you can create hyperlinks to those URLs in Lightdash, like so:

dbt v1.9 and earlier

columns:
  - name: candidate_profile_url
    label: URL of the candidate profile
    meta:
      dimension:
        urls:
          - label: Open in CRM
            url: ${ value.raw }

dbt v1.10+ and Fusion

columns:
  - name: candidate_profile_url
    label: URL of the candidate profile
    config:
      meta:
        dimension:
          urls:
            - label: Open in CRM
              url: ${ value.raw }

Lightdash YAML

dimensions:
  - name: candidate_profile_url
    label: URL of the candidate profile
    urls:
      - label: Open in CRM
        url: ${ value.raw }

How to add custom URLs

By adding custom urls you can configure the actions available to your users. Like linking to external tools, or taking actions in other tools.

In the example below, users can click on a company name and open a corresponding record in their CRM or search for the company in google or open that company’s Slack channel.

dbt v1.9 and earlier

columns:
  - name: company_name
    label: Registered trading name of the company
    meta:
      dimension:
        urls:
          - label: Search for company in Google
            url: 'https://google.com/search?${ value.formatted | url_encode }'
          - label: Open in CRM
            url: 'https://mycrm.com/companies/${ row.company.company_id.raw | url_encode }'

dbt v1.10+ and Fusion

columns:
  - name: company_name
    label: Registered trading name of the company
    config:
      meta:
        dimension:
          urls:
            - label: Search for company in Google
              url: 'https://google.com/search?${ value.formatted | url_encode }'
            - label: Open in CRM
              url: 'https://mycrm.com/companies/${ row.company.company_id.raw | url_encode }'

Lightdash YAML

dimensions:
  - name: company_name
    label: Registered trading name of the company
    urls:
      - label: Search for company in Google
        url: 'https://google.com/search?${ value.formatted | url_encode }'
      - label: Open in CRM
        url: 'https://mycrm.com/companies/${ row.company.company_id.raw | url_encode }'

The ${ value.formatted } will be replaced with the value of the company name in the Lightdash UI at query run time. The ${ row.company.company_id.raw } will be replaced with the value of the company id in the Lightdash UI at query run time. The action will be disabled if the column “company_id” from table “company” is not part of the query.

You can reference values from other columns in your URLs

You can reference another dimension from your table in your URL. For these URLs to work, the other column you’ve referenced needs to be included in your results table. For example, say I’ve added a URL to company_name and it uses the field customer_id:

dbt v1.9 and earlier

columns:
  - name: company_name
    label: Registered trading name of the company
    meta:
      dimension:
        urls:
          - label: "Open company"
            url: "https://example.com/company/${row.customers.customer_id.raw | url_encode }"

dbt v1.10+ and Fusion

columns:
  - name: company_name
    label: Registered trading name of the company
    config:
      meta:
        dimension:
          urls:
            - label: "Open company"
              url: "https://example.com/company/${row.customers.customer_id.raw | url_encode }"

Lightdash YAML

dimensions:
  - name: company_name
    label: Registered trading name of the company
    urls:
      - label: "Open company"
        url: "https://example.com/company/${row.customers.customer_id.raw | url_encode }"

This URL will only work if I have customer_id included in my results table.

Liquid templating

Use templates to configure values dynamically at runtime based on query results.

Available liquid tags

Tag	Description
${ value.formatted }	The exact value of the dimension as seen in the Lightdash UI. For example $1,427.20
${ value.raw }	The raw value of the dimension returned from the underlying SQL query. For example 1427.2
${ row.table_name.column_name.formatted }	The exact value of the column as seen in the Lightdash UI. For example $1,427.20
${ row.table_name.column_name.raw }	The raw value of the dimension returned from the underlying SQL query. For example 1427.2

Available liquid filters

Filters can be used to make small transformations of your values:

• url_encode: Encode a string as URL safe, for example it replaces spaces with %20.

  ${ value.formatted | url_encode }
  

• downcase: Convert a string to lowercase.

  ${ value.formatted | downcase }
  

• append: Append one string to another.

  ${ value.formatted | append: ".html" }
  

There are many more filters available in the Liquid documentation.

Rich text

The richText property allows you to define custom HTML/Markdown templates for displaying dimension and metric values in table cells. This enables sophisticated data presentation with formatting, styling, conditional logic, and external integrations.

Rich text only affects UI display in table cells. It has no impact on value formatting, CSV exports, or the underlying data values.

Basic example

Display a dimension value with custom formatting:

dbt v1.9 and earlier

columns:
  - name: customer_id
    description: 'Unique customer identifier'
    meta:
      dimension:
        richText: |
          **Customer ID:** `${ value.raw }`
          
          [View Profile](https://example.com/customer/${ value.raw })

dbt v1.10+ and Fusion

columns:
  - name: customer_id
    description: 'Unique customer identifier'
    config:
      meta:
        dimension:
          richText: |
            **Customer ID:** `${ value.raw }`
            
            [View Profile](https://example.com/customer/${ value.raw })

Lightdash YAML

dimensions:
  - name: customer_id
    description: 'Unique customer identifier'
    richText: |
      **Customer ID:** `${ value.raw }`
      
      [View Profile](https://example.com/customer/${ value.raw })

Conditional formatting

Use Liquid control flow tags for conditional display based on values:

dbt v1.9 and earlier

columns:
  - name: customer_lifetime_value
    meta:
      metrics:
        average_clv:
          type: average
          richText: |
            {% raw %}{% if value.raw >= 100 %}
            ### 📈 ${ value.formatted }
            **Excellent** Average CLV
            {% elsif value.raw >= 50 %}
            ### 📊 ${ value.formatted }
            **Good** Average CLV
            {% else %}
            ### ⚠️ ${ value.formatted }
            **Low** Average CLV
            {% endif %}{% endraw %}

dbt v1.10+ and Fusion

columns:
  - name: customer_lifetime_value
    config:
      meta:
        metrics:
          average_clv:
            type: average
            richText: |
              {% raw %}{% if value.raw >= 100 %}
              ### 📈 ${ value.formatted }
              **Excellent** Average CLV
              {% elsif value.raw >= 50 %}
              ### 📊 ${ value.formatted }
              **Good** Average CLV
              {% else %}
              ### ⚠️ ${ value.formatted }
              **Low** Average CLV
              {% endif %}{% endraw %}

Lightdash YAML

metrics:
  - name: average_clv
    type: average
    sql: ${customer_lifetime_value}
    richText: |
      {% raw %}{% if value.raw >= 100 %}
      ### 📈 ${ value.formatted }
      **Excellent** Average CLV
      {% elsif value.raw >= 50 %}
      ### 📊 ${ value.formatted }
      **Good** Average CLV
      {% else %}
      ### ⚠️ ${ value.formatted }
      **Low** Average CLV
      {% endif %}{% endraw %}

Liquid templating in rich text

Use templates to configure values dynamically at runtime based on query results.

Available liquid tags

Tag	Description
${ value.formatted }	The exact value of the dimension as seen in the Lightdash UI. For example $1,427.20
${ value.raw }	The raw value of the dimension returned from the underlying SQL query. For example 1427.2
${ row.table_name.column_name.formatted }	The exact value of the column as seen in the Lightdash UI. For example $1,427.20
${ row.table_name.column_name.raw }	The raw value of the dimension returned from the underlying SQL query. For example 1427.2

Available liquid filters

Filters can be used to make small transformations of your values:

• url_encode: Encode a string as URL safe, for example it replaces spaces with %20.

  ${ value.formatted | url_encode }
  

• downcase: Convert a string to lowercase.

  ${ value.formatted | downcase }
  

• append: Append one string to another.

  ${ value.formatted | append: ".html" }
  

There are many more filters available in the Liquid documentation.

Required attributes

Lightdash can use user attributes to limit some dimensions to some users.

In the example below, only users with is_admin attribute true can use the salary dimension on user table. Users without access to this dimension will not see it or the custom metrics created from this dimension on the explore page.

dbt v1.9 and earlier

columns:
  - name:
    description: User name
  - salary:
    description: User salary
    meta:
      dimension:
        required_attributes:
          is_admin: "true"

dbt v1.10+ and Fusion

columns:
  - name:
    description: User name
  - salary:
    description: User salary
    config:
      meta:
        dimension:
          required_attributes:
            is_admin: "true"

Lightdash YAML

dimensions:
  - name: user_name
    description: User name
  - name: salary
    description: User salary
    required_attributes:
      is_admin: "true"

If a user without access to this dimension runs a query that contains this dimension, they will get a Forbidden error.

Any attributes

While required_attributes uses AND logic (all conditions must match), any_attributes uses OR logic — a user only needs to match at least one condition.

dbt v1.9 and earlier

columns:
  - name: salary
    description: User salary
    meta:
      dimension:
        any_attributes:
          department: ["hr", "finance"]
          role: "manager"

dbt v1.10+ and Fusion

columns:
  - name: salary
    description: User salary
    config:
      meta:
        dimension:
          any_attributes:
            department: ["hr", "finance"]
            role: "manager"

Lightdash YAML

dimensions:
  - name: salary
    description: User salary
    any_attributes:
      department: ["hr", "finance"]
      role: "manager"

In this example, users with department = "hr" OR department = "finance" OR role = "manager" can see the salary dimension.

You can combine both required_attributes and any_attributes on the same dimension. When both are set, both checks must pass. See user attributes for details.

Current limitations

Lightdash dimensions and custom metrics are protected by this feature, however, it is possible to write custom SQL to bypass this filter, for example:

• Developers and admins running SQL queries on SQL runner.
• Custom SQL or subqueries on table calculations

Scheduler deliveries will run against the user who created the scheduled delivery, be careful when sharing required attributes with other users.

Color

You can predefine colors for your string type dimensions, these colors will be used instead of your default organization colors for the right value when you use a grouped bar chart or a pie chart.

dbt v1.9 and earlier

  - name: status
    description: "{{ doc(\"orders_status\") }}"
    meta:
      dimension:
        colors:
          "placed": "#e6fa0f"
          "completed": "#558B2F"
          "shipped": "#29B6F6"
          "return_pending": "#FF6F00"
          "returned": "#E91E63"

dbt v1.10+ and Fusion

  - name: status
    description: "{{ doc(\"orders_status\") }}"
    config:
      meta:
        dimension:
          colors:
            "placed": "#e6fa0f"
            "completed": "#558B2F"
            "shipped": "#29B6F6"
            "return_pending": "#FF6F00"
            "returned": "#E91E63"

Lightdash YAML

dimensions:
  - name: status
    description: "Order status"
    colors:
      "placed": "#e6fa0f"
      "completed": "#558B2F"
      "shipped": "#29B6F6"
      "return_pending": "#FF6F00"
      "returned": "#E91E63"

We recommend using #HEX colors, other color types like rgba,rgba or color name (eg: orange) are also supported on charts, but they are not yet supported on the chart config.

You can manually override these dimension colors by going into the chart config and manually picking a color for that serie.

These colors will also take precedence over the organization color palette.

Case sensitive

You can control whether string filters on a dimension are case sensitive or case insensitive. By default, all string filters are case sensitive (case_sensitive: true). When set to false, string filters will ignore case differences when matching values.

This setting affects the following filter operators: equals, not equals, starts with, and ends with.

dbt v1.9 and earlier

columns:
  - name: customer_name
    description: 'Name of the customer'
    meta:
      dimension:
        case_sensitive: false

dbt v1.10+ and Fusion

columns:
  - name: customer_name
    description: 'Name of the customer'
    config:
      meta:
        dimension:
          case_sensitive: false

Lightdash YAML

dimensions:
  - name: customer_name
    description: 'Name of the customer'
    case_sensitive: false

With case_sensitive: false, filtering for “john” would match “John”, “JOHN”, “john”, etc.

Dimension-level case_sensitive settings override explore-level and project-level settings. See Tables reference for explore-level configuration and lightdash.config.yml reference for project-level defaults.

Image Display

Work in Progress: This feature is currently in development and may be subject to changes.

You can configure dimensions to display images in table cells using URL templates. Images are rendered as thumbnails with hover tooltips showing larger previews, perfect for visualizing product images, user avatars, or any other image-based data.

How it works

To display images, you define an image property with a URL template in your dimension or additional dimension configuration. The URL can be dynamic, using LiquidJS templating to construct URLs based on row data and field values.

Simplest example - column already contains image URLs:

If your column already contains complete image URLs, you can simply configure it to display as an image:

dbt v1.9 and earlier

columns:
  - name: image_url
    description: "Image URL for the event"
    meta:
      dimension:
        type: string
        image:
          url: "${value.raw}"

dbt v1.10+ and Fusion

columns:
  - name: image_url
    description: "Image URL for the event"
    config:
      meta:
        dimension:
          type: string
          image:
            url: "${value.raw}"

Lightdash YAML

dimensions:
  - name: image_url
    description: "Image URL for the event"
    type: string
    image:
      url: "${value.raw}"

With custom dimensions and fit:

You can control the size and display behavior of images using width, height, and fit options:

dbt v1.9 and earlier

columns:
  - name: product_image_url
    description: "Product image URL"
    meta:
      dimension:
        type: string
        image:
          url: "${value.raw}"
          width: 100
          height: 100
          fit: "cover"

dbt v1.10+ and Fusion

columns:
  - name: product_image_url
    description: "Product image URL"
    config:
      meta:
        dimension:
          type: string
          image:
            url: "${value.raw}"
            width: 100
            height: 100
            fit: "cover"

Lightdash YAML

dimensions:
  - name: product_image_url
    description: "Product image URL"
    type: string
    image:
      url: "${value.raw}"
      width: 100
      height: 100
      fit: "cover"

Basic example with URL template:

dbt v1.9 and earlier

columns:
  - name: product_id
    meta:
      additional_dimensions:
        product_image:
          type: string
          label: "Product Image"
          description: "Product thumbnail image"
          image:
            url: "https://example.com/images/${value.raw}.jpg"

dbt v1.10+ and Fusion

columns:
  - name: product_id
    config:
      meta:
        additional_dimensions:
          product_image:
            type: string
            label: "Product Image"
            description: "Product thumbnail image"
            image:
              url: "https://example.com/images/${value.raw}.jpg"

Lightdash YAML

dimensions:
  - name: product_id
  - name: product_image
    type: string
    label: "Product Image"
    description: "Product thumbnail image"
    image:
      url: "https://example.com/images/${value.raw}.jpg"

Advanced example with dynamic URLs:

dbt v1.9 and earlier

columns:
  - name: event_type
    meta:
      additional_dimensions:
        event_image:
          type: string
          label: "Event Image"
          description: "Event banner image"
          image:
            url: "https://cdn.example.com/${value.raw}-${row.events.event_id.raw | upcase}.png"

dbt v1.10+ and Fusion

columns:
  - name: event_type
    config:
      meta:
        additional_dimensions:
          event_image:
            type: string
            label: "Event Image"
            description: "Event banner image"
            image:
              url: "https://cdn.example.com/${value.raw}-${row.events.event_id.raw | upcase}.png"

Lightdash YAML

dimensions:
  - name: event_type
  - name: event_image
    type: string
    label: "Event Image"
    description: "Event banner image"
    image:
      url: "https://cdn.example.com/${value.raw}-${row.events.event_id.raw | upcase}.png"

Display behavior

• Thumbnails: Images display as thumbnails in table cells (default: 32px height)
• Hover preview: Hovering over a thumbnail reveals a larger preview via tooltip
• Error handling: Failed image loads show a photo-off icon with error details in the tooltip
• Validation: Invalid URL syntax is caught and displays an error state

Image configuration properties

The image object supports the following properties:

Property	Type	Default	Description
url	string	(required)	The image URL. Supports LiquidJS templating with ${value.raw}, ${row.table.column.raw}, etc.
width	number	auto	Image width in pixels. When specified without height, height defaults to ‘auto’ to maintain aspect ratio.
height	number	32	Image height in pixels.
fit	string	”cover”	Controls how the image fits within the dimensions. Options: "cover", "contain", "fill", or "none".

Fit options:

• cover (default) - Image fills the space while maintaining aspect ratio. May crop content.
• contain - Scales image to fit within dimensions while preserving aspect ratio. No cropping.
• fill - Stretches image to fill dimensions. May distort aspect ratio.
• none - Displays image at its original size without scaling.

Examples:

# Square thumbnail with cover fit
image:
  url: "${value.raw}"
  width: 50
  height: 50
  fit: "cover"

# Wide thumbnail maintaining aspect ratio
image:
  url: "https://example.com/images/${value.raw}.jpg"
  width: 100
  # height defaults to 'auto' to maintain aspect ratio

# Original size display
image:
  url: "${value.raw}"
  fit: "none"

URL Templating

The image.url property supports LiquidJS templating with the same tags and filters available for dimension URLs:

Available liquid tags:

Tag	Description
${ value.formatted }	The exact value of the dimension as seen in the Lightdash UI
${ value.raw }	The raw value of the dimension returned from the underlying SQL query
${ row.table_name.column_name.formatted }	The exact value of another column as seen in the Lightdash UI
${ row.table_name.column_name.raw }	The raw value of another dimension returned from the underlying SQL query

Available liquid filters:

You can use liquid filters to transform values:

image:
  url: "https://example.com/${value.raw | downcase}.jpg"

Current limitations

• Dimensions only: Image display is currently supported for dimensions and additional dimensions only (not metrics or table calculations)
• Referenced columns: When using ${ row.table_name.column_name } templates, the referenced column must be included in your results table for the image to display

Example: Product catalog with images

dbt v1.9 and earlier

models:
  - name: products
    columns:
      - name: sku
        description: "Product SKU code"
        meta:
          dimension:
            type: string
          additional_dimensions:
            product_thumbnail:
              type: string
              label: "Product Image"
              description: "Product catalog image"
              image:
                url: "https://cdn.mystore.com/products/${value.raw}/thumbnail.jpg"
                width: 80
                height: 80
                fit: "cover"
      - name: category
        description: "Product category"
        meta:
          dimension:
            type: string
          additional_dimensions:
            category_icon:
              type: string
              label: "Category Icon"
              description: "Category icon image"
              image:
                url: "https://cdn.mystore.com/icons/${value.raw | downcase}.png"
                width: 40
                height: 40
                fit: "contain"
      - name: hero_image_url
        description: "Product hero image URL"
        meta:
          dimension:
            type: string
            image:
              url: "${value.raw}"
              width: 120
              fit: "cover"

dbt v1.10+ and Fusion

models:
  - name: products
    columns:
      - name: sku
        description: "Product SKU code"
        config:
          meta:
            dimension:
              type: string
            additional_dimensions:
              product_thumbnail:
                type: string
                label: "Product Image"
                description: "Product catalog image"
                image:
                  url: "https://cdn.mystore.com/products/${value.raw}/thumbnail.jpg"
                  width: 80
                  height: 80
                  fit: "cover"
      - name: category
        description: "Product category"
        config:
          meta:
            dimension:
              type: string
            additional_dimensions:
              category_icon:
                type: string
                label: "Category Icon"
                description: "Category icon image"
                image:
                  url: "https://cdn.mystore.com/icons/${value.raw | downcase}.png"
                  width: 40
                  height: 40
                  fit: "contain"
      - name: hero_image_url
        description: "Product hero image URL"
        config:
          meta:
            dimension:
              type: string
              image:
                url: "${value.raw}"
                width: 120
                fit: "cover"

Lightdash YAML

type: model
name: products

dimensions:
  - name: sku
    description: "Product SKU code"
    type: string
  - name: product_thumbnail
    type: string
    label: "Product Image"
    description: "Product catalog image"
    image:
      url: "https://cdn.mystore.com/products/${value.raw}/thumbnail.jpg"
      width: 80
      height: 80
      fit: "cover"
  - name: category
    description: "Product category"
    type: string
  - name: category_icon
    type: string
    label: "Category Icon"
    description: "Category icon image"
    image:
      url: "https://cdn.mystore.com/icons/${value.raw | downcase}.png"
      width: 40
      height: 40
      fit: "contain"
  - name: hero_image_url
    description: "Product hero image URL"
    type: string
    image:
      url: "${value.raw}"
      width: 120
      fit: "cover"

Using special characters or capital letters in your column names

If you use special characters on your column names, you might get errors when using those columns on explore. For example, having a column named Status with capital S on a table named orders in postgres throws the following error:

column orders.status does not exist

To fix this, we can add the quoted column to our sql meta tag on dimensions

dbt v1.9 and earlier

- name: status
  meta:
    dimension:
      type: string
      sql: '"orders"."Status"' # you can also use '${TABLE}."Status"'

dbt v1.10+ and Fusion

- name: status
  config:
    meta:
      dimension:
        type: string
        sql: '"orders"."Status"' # you can also use '${TABLE}."Status"'

Lightdash YAML

dimensions:
  - name: status
    type: string
    sql: '"orders"."Status"' # you can also use '${TABLE}."Status"'

This will quote the Status columns on the SQL query

SELECT
  "orders".order_id AS "orders_order_id",
  "orders"."Status" AS "orders_status"
FROM "postgres"."jaffle"."orders" AS "orders"

Additional dimensions

Additional dimensions let you define multiple dimensions off of a single column from your dbt model. This is useful when adding different formatting to a column, comparing or combining columns, parsing JSON columns, or creating persisted groups/buckets based off of a column.

A “normal” dimension is a column created in your .sql file in dbt that is written to your data warehouse. An additional dimension is not included in your dbt .sql file, so it’s not written to your data warehouse. When used in Lightdash, it just adds the dimension definition to your SQL query (so it’s “created” at runtime).

All dimension configurations are available for additional dimensions. You can also use additional dimensions when defining metrics.

Additional dimensions names need to be unique in the model.

Adding different formatting

dbt v1.9 and earlier

columns:
  - name: revenue
    meta:
      dimension:
        type: number
      additional_dimensions:
        revenue_in_thousands:
          type: number
          format: '#,##0," K"'
        revenue_in_millions:
          type: number
          format: '#,##0,," M"'

dbt v1.10+ and Fusion

columns:
  - name: revenue
    config:
      meta:
        dimension:
          type: number
        additional_dimensions:
          revenue_in_thousands:
            type: number
            format: '#,##0," K"'
          revenue_in_millions:
            type: number
            format: '#,##0,," M"'

Lightdash YAML

dimensions:
  - name: revenue
    type: number
  - name: revenue_in_thousands
    type: number
    sql: ${TABLE}.revenue
    format: '#,##0," K"'
  - name: revenue_in_millions
    type: number
    sql: ${TABLE}.revenue
    format: '#,##0,," M"'

Comparing or combining columns

When defining additional dimensions, you can reference other dimensions, even from joined tables (organizations is a joined table in the example below).

dbt v1.9 and earlier

columns:
  - name: created_date
    meta:
      dimension:
        type: date
      additional_dimensions:
        days_to_first_query_run:
          type: number
          description: 'Number of days between a user being created and their first query run.'
          sql: ${first_query_date} - ${created_date}
        days_to_organization_first_payment:
          type: number
          description: 'Number of days between a user being created and their organization making its first payment. This will be negative for users who joined after the first payment.'
          sql: ${created_date} - ${organizations.first_payment_date}

dbt v1.10+ and Fusion

columns:
  - name: created_date
    config:
      meta:
        dimension:
          type: date
        additional_dimensions:
          days_to_first_query_run:
            type: number
            description: 'Number of days between a user being created and their first query run.'
            sql: ${first_query_date} - ${created_date}
          days_to_organization_first_payment:
            type: number
            description: 'Number of days between a user being created and their organization making its first payment. This will be negative for users who joined after the first payment.'
            sql: ${created_date} - ${organizations.first_payment_date}

Lightdash YAML

dimensions:
  - name: created_date
    type: date
  - name: days_to_first_query_run
    type: number
    description: 'Number of days between a user being created and their first query run.'
    sql: ${first_query_date} - ${created_date}
  - name: days_to_organization_first_payment
    type: number
    description: 'Number of days between a user being created and their organization making its first payment. This will be negative for users who joined after the first payment.'
    sql: ${created_date} - ${organizations.first_payment_date}

Parsing JSON columns

Usually you’ll want to add hidden:true for the main JSON dimension since raw JSON is not useful in charts.

dbt v1.9 and earlier

columns:
  - name: metadata # this is a jsonb column with metadata
    meta:
      dimension:
        hidden: true
      additional_dimensions:
        version:
          type: number
          sql: JSON_VALUE(${metadata}, '$.version') # custom SQL applied to get the "version" value inside metadata

dbt v1.10+ and Fusion

columns:
  - name: metadata # this is a jsonb column with metadata
    config:
      meta:
        dimension:
          hidden: true
        additional_dimensions:
          version:
            type: number
            sql: JSON_VALUE(${metadata}, '$.version') # custom SQL applied to get the "version" value inside metadata

Lightdash YAML

dimensions:
  - name: metadata # this is a jsonb column with metadata
    hidden: true
  - name: version
    type: number
    sql: JSON_VALUE(${metadata}, '$.version') # custom SQL applied to get the "version" value inside metadata

Adding multiple timezones for the same dimension

You can use additional dimensions to convert a timestamp into multiple timezones:

dbt v1.9 and earlier

columns:
  - name: created_at
    description: 'The time that the thing was created'
    meta:
      dimension:
        label: 'Created (UTC)'
        type: timestamp
      additional_dimensions:
        created_at_est:
          type: timestamp
          label: 'Created (EST)'
          description: 'The time that the thing was created, in EST'
          sql: "convert_timezone('UTC', 'America/New_York', ${TABLE}.created_at)"

dbt v1.10+ and Fusion

columns:
  - name: created_at
    description: 'The time that the thing was created'
    config:
      meta:
        dimension:
          label: 'Created (UTC)'
          type: timestamp
        additional_dimensions:
          created_at_est:
            type: timestamp
            label: 'Created (EST)'
            description: 'The time that the thing was created, in EST'
            sql: "convert_timezone('UTC', 'America/New_York', ${TABLE}.created_at)"

Lightdash YAML

dimensions:
  - name: created_at
    description: 'The time that the thing was created'
    label: 'Created (UTC)'
    type: timestamp
  - name: created_at_est
    type: timestamp
    label: 'Created (EST)'
    description: 'The time that the thing was created, in EST'
    sql: "convert_timezone('UTC', 'America/New_York', ${TABLE}.created_at)"

Using additional dimensions in metrics

To define metrics based on additional dimensions, you need to add them to the model’s meta metrics, or use custom SQL in defining them under the column’s meta.

dbt v1.9 and earlier

models:
  - name: users
    meta:
      metrics:
        highest_version_model_metric_example:
          type: max
          sql: ${version}
    columns:
      - name: metadata
        meta:
          dimension:
            hidden: true
          additional_dimensions:
            version:
              type: number
              sql: JSON_VALUE(${metadata}, '$.version')
          metrics:
            highest_version:
              type: max
              sql: ${version}

dbt v1.10+ and Fusion

models:
  - name: users
    config:
      meta:
        metrics:
          highest_version_model_metric_example:
            type: max
            sql: ${version}
      columns:
        - name: metadata
          meta:
            dimension:
              hidden: true
            additional_dimensions:
              version:
                type: number
                sql: JSON_VALUE(${metadata}, '$.version')
            metrics:
              highest_version:
                type: max
                sql: ${version}

Lightdash YAML

type: model
name: users

dimensions:
  - name: metadata
    hidden: true
  - name: version
    type: number
    sql: JSON_VALUE(${metadata}, '$.version')

metrics:
  highest_version_model_metric_example:
    type: max
    sql: ${version}
  highest_version:
    type: max
    sql: ${version}

Referencing time intervals in additional dimensions

You can reference time interval dimensions within additional dimensions. This is useful for creating custom logic based on specific time intervals.

For example, you can create a tier based on whether a specific time interval has a value:

dbt v1.9 and earlier

  - name: session_start
    meta:
      dimension:
        type: timestamp
        time_intervals:
        - DAY_OF_WEEK_NAME
        - WEEK
        - MONTH
        - RAW
        - DAY
        - HOUR_OF_DAY_NUM
        - QUARTER
      additional_dimensions:
        extra_session_start_tier:
          type: string
          sql: |
            CASE
              WHEN ${session_start_month} IS NOT NULL THEN 'month'
              ELSE 'else' END

dbt v1.10+ and Fusion

  - name: session_start
    config:
      meta:
        dimension:
          type: timestamp
          time_intervals:
          - DAY_OF_WEEK_NAME
          - WEEK
          - MONTH
          - RAW
          - DAY
          - HOUR_OF_DAY_NUM
          - QUARTER
        additional_dimensions:
          extra_session_start_tier:
            type: string
            sql: |
              CASE
                WHEN ${session_start_month} IS NOT NULL THEN 'month'
                ELSE 'else' END

Lightdash YAML

dimensions:
  - name: session_start
    type: timestamp
    time_intervals:
    - DAY_OF_WEEK_NAME
    - WEEK
    - MONTH
    - RAW
    - DAY
    - HOUR_OF_DAY_NUM
    - QUARTER
  - name: extra_session_start_tier
    type: string
    sql: |
      CASE
        WHEN ${session_start_month} IS NOT NULL THEN 'month'
        ELSE 'else' END

In this example, the additional dimension extra_session_start_tier references ${session_start_month}, which is the MONTH time interval of the session_start dimension.