Earlier this year, we announced a public preview of period-over-period (PoP) measures in LookML and we have appreciated the feedback from everyone who started using the new PoP measure and reached out to share their thoughts. We are pleased to announce period-over-period measures are now generally available as of Looker 25.14.
With this release, we have new functionality that will enable you to use period-over-period measures for broader use cases. We introduced the value_to_date subparameter to indicate whether Looker should calculate the values for the PoP measure by using the amount of time that has elapsed in the current timeframe at the time the query is run.
The value_to_date subparameter can be no (default) or yes:
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no will assume the whole timeframe window when aggregating data.
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yes will calculate the amount of time observed in the current period and apply it to the PoP measure (e.g. YTD in 2024 vs YTD in 2025).
We also expanded dialect support for PoP measures to MySQL 8 and you can now use PoP measures with all the aggregate measure types that Looker supports. We enhanced usability of the new measures by no longer requiring that you select the relevant based_on_time dimension in the explore itself. Instead, you can just use it as a filter which helps to simplify creating visualizations.
We’re also introducing synonyms, a new LookML parameter that lets you specify a list of words or phrases to help large language models or application developers understand other ways that users may refer to a field. For example, you could define synonyms like “customer,” “shopper,” or “purchaser” for your users field. This ensures that no matter how a user phrases their query, the underlying data field is correctly identified, reducing the need for the LLM to guess or infer the user’s intent, leading to more reliable and accurate conversations. This proactive approach helps mitigate ambiguity and ensures the LLM’s output is grounded in the actual data structure, directly preventing hallucinations and improving the accuracy of the analysis.
We hope you find these new enhancements valuable in your organization and will continue to build out more enhancements for PoP measures and LookML more broadly. Stay tuned for more updates from the world of Looker.
