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Period comparison (beta)

This feature is currently in beta.We’re actively testing and improving it.
We’ve made significant improvements to how you generate period-over-period comparisons. You can now customize a PoP metric’s series type, label, show value labels, and more. To add a period comparison:
  1. Select a time/date dimension
  2. Select a metric
  3. On the results table, click on a metric’s column and select Add period comparison
  4. Choose the time dimension and offset, then hit save
  5. Add the generated metric to your chart
You can also ask an AI agent for comparisons in natural language — for example, “compare revenue to last month” or “year-over-year orders by week”.

Period-over-period analysis is one of the most common ways to evaluate how metrics change over time. Whether you’re looking at month-over-month growth, year-over-year comparisons, or week-over-week performance, Lightdash makes it easy to build these analyses directly in your dashboards. This guide walks through several examples of how to do period-over-period analysis in Lightdash. You can also watch the video walkthrough if you’d prefer a visual demo.

Big Value Charts: Simple Comparisons

The fastest way to get started is with the Big Value chart type.

Month-over-month

  • Pull two months of data.
  • Use the Big Value chart and select Compare to previous row
  • Lightdash automatically shows the comparison.
That’s it!

Same month, previous Year

  • Pull ~13 months of data with MONTH and MONTH_NUM time dimensions and your metric.
  • Create a table calculation to filter only the current month and the same month last year:
This table calculation relies on the MONTH_NUM time interval.
  • Filter where the value of this table calculation is true.
  • Then use the Big Value chart with Compare to previous row

Trend line comparisons

Sometimes you need more than a single value—you want to see how trends evolve.

By week of year

  • Add week of year time dimension (1-52) on the X-axis.
  • Plot the metric (e.g. event_count).
  • Group by year.
  • This allows you to compare trends across years.
Check minute 1:45 in the Loom video for an example.
Bonus: if you want a more business-user-friendly version you can use the table calculation below to add descriptions for each week number to get a chart like this.

By day of month with running totals

  • Compare June vs July (or any two months).
  • Use day of month time dimension (1-31) on the X-axis, grouped by month.
  • Add a running total table calculation.
  • Optionally, use bars in the background to show cumulative progress.
Check minute 2:30 in the Loom video for an example.

Compare arbitrary weeks

You can also compare arbitrary weeks side by side.
  • Select specific weeks (e.g. 2, 8, 12).
  • Use week of year as the grouping dimension.
  • Apply a running total to see how each week accumulates.
  • This shows how different weeks trend across the same range.
Check minute 3:00 in the Loom video for an example.

Year-over-year by month

For a full year-over-year comparison across months:
  1. Pull two years worth of monthly of data.
  2. Use the lag() function in a table calculation to find the value from the same month last year:
  1. Create a percent change calculation:
  1. Filter out rows where previous_year_value is null.
Check minute 3:45 in the Loom video for an example.

Using parameters for period-over-period analysis

Parameters let you create dynamic period-over-period comparisons in your charts and dashboards. Users can easily toggle between different date ranges to see how metrics are tracking over time — no need to rebuild charts or manually adjust filters. For more on working with parameters, check out our parameters reference guide. This guide walks through an example of how to do period-over-period analysis in Lightdash using parameters, alternatively you can watch our demo tutorial below.
Say you want users to select a time period like yesterday, last 7 days, or last 30 days, and then compare the current period to both the previous period and the same period a year ago. To do this, you:
1

Set up your date range / period parameter

Date range period parameter syntax

You can also take a look at the Date Range parameter setup in our demo dbt project here.
2

Create a dimension to categorize date periods

Next, you need to create an additional dimension inside the dbt_orders model that calculates the period selected in the date_range parameter using conditional case statements.

Additional dimension syntax

You can also take a look at the order_date_period dimension setup in our demo dbt project here.
3

Build your chart with the period dimension

To create a chart that uses your period parameter, you would need to:
  • select the Order date period additional dimension and the Order count metric
  • specify that order_date_period is not out of range
  • you can optionally filter out other date range groups e.g. you might want to filter out previous year if you want to create a big value chart that compares current period to previous period.
4

Add your chart to a dashboard

You can then add this chart to a dashboard. Users can select an option from the Date Range parameter and the charts will automatically update to display the selected period.

Custom date range example

Similar to above, you can also set up a custom date range parameter that allows users to select specific start and end dates for their analysis. Below is the code needed for the parameter and the additional dimension to categorize the date periods for a custom date range:

Custom date range parameter configuration

Custom date range additional dimension code

The code examples above will give you the following parameter options in the Lightdash UI that will output the custom period labels shown in the chart: