Add an Image: filtering by suggestion "kind" or "confidence"
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	KStoller-WMF
	Jul 1 2024, 9:14 PM

Description

User Story:

As a newcomer editing Wikipedia, I want to receive task suggestions that are fairly accurate and structured, so that I can get started and successfully edit on a mobile device.

Documentation:

https://www.mediawiki.org/wiki/Platform_Engineering_Team/Data_Value_Stream/Data_Gateway#Image_Suggestions
https://www.mediawiki.org/wiki/Help:Growth/Tools/Add_an_image
https://www.mediawiki.org/wiki/Growth/Personalized_first_day/Structured_tasks/Add_an_image

Background:

Structured tasks provide new editors with machine generated suggestions and structured the edit in a way that helps more new account holders edit constructively (1).

We tested initial suggestions with our pilot wikis to ensure the tasks provide good suggestions the majority of the time. Task onboarding indicates that suggestions aren't always correct, and that's why editors are asked to review the suggestions. In other words, we don't expect the suggestions to be 100% accurate, but they should be good suggestions ~70% of the time.

However, as we looked into scaling "add an image" to more wikis, we completed an additional round of evaluation:
T366925: Evaluate image suggestions for a new set of Wikipedias.

When reviewing these suggestions it seemed that certain suggestion "kinds" were less likely to be good suggestions. The istype-depicts and istype-commons-category suggestions were often lower quality. After removing these task kinds from the suggestion pool, we notice suggestions improve.

The downside of removing these suggestions is that the task pool is reduced dramatically.

Open questions:

Should we remove istype-depicts and istype-commons-category task kinds from certain wikis or all wikis?
Should these suggestions be removed from both the article-level and section-level tasks?
Should we simply allow for filtering based on confidence score?
Should we allow communities to adjust this within Community Configuration?
Should we allow communities to adjust the confidence level for "add an image" tasks?

Acceptance Criteria:

TBD

Details

Other Assignee: mfossati

Related Changes in GitLab:

	Title	Reference	Author	Source Branch	Dest Branch
	add concatenate and exists	repos/structured-data/image-suggestions-data-pipelines!9	a-pizzata	T368987-fix-values-content	main

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Status	Assigned	Task
Open	KStoller-WMF	T322592 [EPIC] Deploy "add an image" to all Wikipedias
Stalled	Trizek-WMF	T360059 Communication around scaling "add an image" to more Wikipedias
Open	None	T360060 Scale Article-Level "add an image" to more Wikipedias
Open	APizzata-WMF	T368987 Add an Image: filtering by suggestion "kind" or "confidence"

Event Timeline

KStoller-WMF created this task.Jul 1 2024, 9:14 PM

KStoller-WMF triaged this task as Medium priority.Jul 1 2024, 9:22 PM

KStoller-WMF mentioned this in T360060: Scale Article-Level "add an image" to more Wikipedias.

KStoller-WMF moved this task from Inbox to Needs Discussion on the Growth-Team board.

Trizek-WMF mentioned this in T360059: Communication around scaling "add an image" to more Wikipedias.Jul 3 2024, 3:26 PM

Michael subscribed.Jul 25 2024, 7:34 PM

Moving to triaged for now, we want to focus on this in the future but we need to focus on Q1 priorities for now.

Notes from discussion:

Ideally communities could adjust this via Community Configuration in case they notice poor suggestions based on "kind" or "confidence" suggestions.

KStoller-WMF removed a project: Growth-Structured-Tasks.Dec 11 2025, 6:05 PM

KStoller-WMF updated the task description. (Show Details)

Chiming with a suggested workflow that is currently actionable.
Given a new target Wikipedia:

internally evaluate a sample of suggestions with https://alis-evaluation.toolforge.org/ as in T381930: Test the "Add an Image" Structured Task on a Representative Sample of Wikipedias
the data gateway API provides kind as a list and confidence as a score for every suggestion. Determine eventual kinds to filter and a confidence threshold
apply those filters after calling the API

We recently discussed optimizing the filtering step. This requires a change to how flags indicating whether a Wikipedia article has any suggestions are sent to search indices: given an article, update its recommendation.image and recommendation.image_section weighted tags with the value of the highest confidence score available.

In T368987#11454246, @mfossati wrote:

We recently discussed optimizing the filtering step. This requires a change to how flags indicating whether a Wikipedia article has any suggestions are sent to search indices: given an article, update its recommendation.image and recommendation.image_section weighted tags with the value of the highest confidence score available.

See https://wikimedia.slack.com/archives/C01DFVAQRGA/p1764065493353579?thread_ts=1763992906.169429&cid=C01DFVAQRGA

KStoller-WMF added a subscriber: DMburugu.Dec 12 2025, 4:15 PM

Currently the indexed search tags have a hard-coded value named exists but it could be something else, (if deemed useful at search time) tags related to image recommendations could be more granular by including the kind as separate tags.
At query time this would become (suggested syntax): hasrecommendation:image=istype-depicts.

hasrecommendation:image>0.8 -hasrecommendation:image=istype-depicts could filter recommendations with a score above 0.8 and without a istype-depicts kind.

In T368987#11552675, @dcausse wrote:

Currently the indexed search tags have a hard-coded value named exists but it could be something else, (if deemed useful at search time) tags related to image recommendations could be more granular by including the kind as separate tags.
At query time this would become (suggested syntax): hasrecommendation:image=istype-depicts.

hasrecommendation:image>0.8 -hasrecommendation:image=istype-depicts could filter recommendations with a score above 0.8 and without a istype-depicts kind.

As I understand it, but I might be wrong (looking to @mfossati to correct me if needed), the score already represents the source of the recommendation:

0.9 = image is already used for that article on another Wikipedia
0.8 = image is used as P18 on the linked Wikidata Item
0.7 = image either has a matching commons category or matching depicts statement on commons

So, it should be enough if we are able to say hasrecommendation:image>=0.8 in our search query to exclude the lowest category.

In T368987#11553103, @Michael wrote:

the score already represents the source of the recommendation:

Roughly speaking, yes. It's a function of sources. ALIS and SLIS have different implementations, though.

0.9 = image is already used for that article on another Wikipedia

0.8 = image is used as P18 on the linked Wikidata Item

0.7 = image either has a matching commons category or matching depicts statement on commons

This should be the correct list for ALIS:

90 = Wikidata image
80 = Commons category or Wikipedia lead image
70 = Commons depicts statement

So, it should be enough if we are able to say hasrecommendation:image>=0.8 in our search query to exclude the lowest category.

I agree, along the lines of T405059: Adapt hasrecommendation to filter by score and possibly rank by score.

In T368987#11565586, @mfossati wrote:

In T368987#11553103, @Michael wrote:

0.9 = image is already used for that article on another Wikipedia

0.8 = image is used as P18 on the linked Wikidata Item

0.7 = image either has a matching commons category or matching depicts statement on commons

This should be the correct list for ALIS:

90 = Wikidata image

80 = Commons category or Wikipedia lead image

70 = Commons depicts statement

Oh, that is interesting, thank you for clarifying! For 80, I assume you mean "(Commons category or Wikipedia) lead image" and not "(Commons category) or (Wikipedia lead image)", correct?

Ahoelzl assigned this task to APizzata-WMF.Jan 30 2026, 6:42 PM

Ahoelzl added a project: Data-Engineering (Q3 FY25/26 January 1st - March 31th).

mfossati updated Other Assignee, added: mfossati.Feb 2 2026, 10:25 AM

In T368987#11565931, @Michael wrote:

For 80, I assume you mean "(Commons category or Wikipedia) lead image" and not "(Commons category) or (Wikipedia lead image)", correct?

Not sure what you mean here, but let me expand: given a Wikipedia article X (candidate for receiving suggestions) and its corresponding Wikidata item Q, Commons category means an image coming from Q's P373 property (see examples); Wikipedia lead image means the lead image of a sitelink of X, i.e., an equivalent article in another language.

In T368987#11573174, @mfossati wrote:

In T368987#11565931, @Michael wrote:

For 80, I assume you mean "(Commons category or Wikipedia) lead image" and not "(Commons category) or (Wikipedia lead image)", correct?

Not sure what you mean here, but let me expand: given a Wikipedia article X (candidate for receiving suggestions) and its corresponding Wikidata item Q, Commons category means an image coming from Q's P373 property (see examples); Wikipedia lead image means the lead image of a sitelink of X, i.e., an equivalent article in another language.

Let's take the example of Gorilla from that list of examples that you linked. What I'm asking is:
Does the alogorithm suggest with a score of 80

A) the specific file https://commons.wikimedia.org/wiki/File:Lowland_Gorilla_(8973697544).jpg which is the "lead image" of the category linked on the respective Wikidata Item

B) any of the 40+ images that are directly in the category of Gorilla

C) something else

A) would make much more sense to me than B), because images in the category seem to be still very "divers" and many are much less ideal or even suitable for being the first image to illustrate an articles about Gorrilas than the one specific lead/infobox image of that category.

APizzata-WMF moved this task from Next Up to In progress on the Data-Engineering (Q3 FY25/26 January 1st - March 31th) board.Feb 12 2026, 10:35 AM

KStoller-WMF mentioned this in T418295: Add-an-image on desktop.Mar 8 2026, 10:00 PM

APizzata-WMF moved this task from In progress to Ready to Deploy on the Data-Engineering (Q3 FY25/26 January 1st - March 31th) board.Mon, Mar 23, 10:33 AM

Merged the MR, waiting for tomorrow's run to validate.

ALIS run correctly and here the results:

spark.sql(
    """
    SELECT
        tag,
        COUNT(*) AS cnt
    FROM analytics_platform_eng.image_suggestions_search_index_delta
    WHERE snapshot = '2026-03-16'
    GROUP BY tag
    """
).show()

+--------------------+--------+
|                 tag|count(1)|
+--------------------+--------+
|recommendation.image| 4041911|
+--------------------+--------+

spark.sql(
    """
    SELECT *
    FROM analytics_platform_eng.image_suggestions_search_index_delta
    WHERE snapshot = '2026-03-16'
       AND tag = 'recommendation.image'
    """
).show()

+-----------+--------------+-------+--------------------+------+----------+
|     wikiid|page_namespace|page_id|                 tag|values|  snapshot|
+-----------+--------------+-------+--------------------+------+----------+
|aawikibooks|             0|      1|recommendation.image| [970]|2026-03-16|
|     abwiki|             0|   2441|recommendation.image| [980]|2026-03-16|
|     abwiki|             0|   2443|recommendation.image| [980]|2026-03-16|
|     abwiki|             0|   2444|recommendation.image| [980]|2026-03-16|
|     abwiki|             0|   2445|recommendation.image| [980]|2026-03-16|
|     abwiki|             0|   2451|recommendation.image| [980]|2026-03-16|
|     abwiki|             0|   2455|recommendation.image| [800]|2026-03-16|
|     abwiki|             0|   2460|recommendation.image| [800]|2026-03-16|
|     abwiki|             0|   2521|recommendation.image| [800]|2026-03-16|
|     abwiki|             0|   2527|recommendation.image| [800]|2026-03-16|
|     abwiki|             0|   2528|recommendation.image| [800]|2026-03-16|

spark.sql(
    """
    SELECT
        min(values) AS min_values,
        max(values) AS max_values
    FROM analytics_platform_eng.image_suggestions_search_index_delta
    WHERE snapshot = '2026-03-16'
      AND tag = 'recommendation.image'
      AND NOT array_contains(values, '__DELETE_GROUPING__')
    """
).show()

+-----------+-----------+
|min(values)|max(values)|
+-----------+-----------+
|      [700]|      [990]|
+-----------+-----------+

mfossati awarded a token.Thu, Mar 26, 5:38 PM

Also SLIS results look like intended:

spark.sql(
    """
    SELECT
        tag,
        MIN(values) AS min_values,
        MAX(values) AS max_values
    FROM analytics_platform_eng.image_suggestions_search_index_full
    WHERE snapshot = '2026-03-16'
      AND NOT array_contains(values, '__DELETE_GROUPING__')
    GROUP BY tag
    """
).show(truncate=False)

+--------------------------------------+-----------------+-----------+
|tag                                   |min(values)      |max(values)|
+--------------------------------------+-----------------+-----------+
|image.linked.from.wikidata.p18        |[Q100000001|1000]|[Q99|1000] |
|image.linked.from.wikipedia.lead_image|[Q100000034|1]   |[Q99|43]   |
|recommendation.image                  |[700]            |[990]      |
|recommendation.image_section          |[710]            |[970]      |
+--------------------------------------+-----------------+-----------+

spark.sql(
    """
    SELECT
        tag,
        COUNT(*) AS cnt
    FROM analytics_platform_eng.image_suggestions_search_index_full
    WHERE snapshot = '2026-03-16'
      AND NOT array_contains(values, '__DELETE_GROUPING__')
    GROUP BY tag
    """
).show(truncate=False)

+--------------------------------------+--------+
|tag                                   |count(1)|
+--------------------------------------+--------+
|recommendation.image_section          |323501  |
|image.linked.from.wikidata.p18        |5871736 |
|image.linked.from.wikipedia.lead_image|7171983 |
|recommendation.image                  |4040426 |
+--------------------------------------+--------+

spark.sql(
    """
    SELECT
        tag,
        COUNT(*) AS cnt
    FROM analytics_platform_eng.image_suggestions_search_index_delta
    WHERE snapshot = '2026-03-16'
      AND NOT array_contains(values, '__DELETE_GROUPING__')
    GROUP BY tag
    """
).show(truncate=False)

+--------------------+--------+
|tag                 |count(1)|
+--------------------+--------+
|recommendation.image|4040426 |
+--------------------+--------+

@APizzata-WMF sorry I did not spot this earlier but the values ["970"] is not correct, it unfortunately pushed the string 970 as the tag value instead of the score, the tag value must remain exists with the score appended after a |: the full string should look like ["exists|970"].
Is this possible to re-run the pipeline with such fix applied, I'll re-ship the tags right after.

Hey @dcausse I must have misunderstood and thought the exists| part could be removed. I can update the output of the tables to show the correct form and fix the code to show in the correct form from next run. Does this sound good to you?

In T368987#11763303, @APizzata-WMF wrote:

Hey @dcausse I must have misunderstood and thought the exists| part could be removed. I can update the output of the tables to show the correct form and fix the code to show in the correct form from next run. Does this sound good to you?

yes, ideally we should overwrite the 2026-03-16 snapshot with proper values so that we can re-ship tags (all suggestions might have disappeared from the structured tasks point of view), please feel free to add me as a reviewer. thanks!

I think one of the cause of this confusion is the current contract between ALIS/SLIS and search, for historical reasons (first non-search pipeline to push data to search indices) it used search internal formats which are very fragile (magic words like __DELETE_GROUPING__ and tag/score internal string encoding). I filed T414099 to try to address some of this by updating the ALIS/SLIS pipeline to use a newer contract based on an event schema which is what newer pipelines are using (i.e. revise tone recommendations).

I have created and validated all my update commands, will shortly run them all and past here all the results with the validations. As a next step we can just rerun the image_suggestions_weekly dag correct?

In T368987#11763867, @APizzata-WMF wrote:

I have created and validated all my update commands, will shortly run them all and past here all the results with the validations. As a next step we can just rerun the image_suggestions_weekly dag correct?

Yes we can just clear the publish_page_change_weighted_tags task, it should rerun it.

a-pizzata opened https://gitlab.wikimedia.org/repos/structured-data/image-suggestions-data-pipelines/-/merge_requests/9

add concatenate and exists

Unfortunately, due to permission on the delta and full tables, I was not able to update the faulty records. Therefore here is the MR that should fix it, I will run it locally and test the results (will post here) and merge ASAP.

a-pizzata closed https://gitlab.wikimedia.org/repos/structured-data/image-suggestions-data-pipelines/-/merge_requests/9

add concatenate and exists

a-pizzata reopened https://gitlab.wikimedia.org/repos/structured-data/image-suggestions-data-pipelines/-/merge_requests/9

add concatenate and exists

Tested in the dev env and the results are good:

spark.sql("""
select tag,count(*) from  analytics_platform_eng.image_suggestions_search_index_full
where snapshot = '2026-03-16' and tag in ('recommendation.image','recommendation.image_section')
group by tag""").show()

+----------------------------+--------+
|tag                         |count(1)|
+----------------------------+--------+
|recommendation.image        |4040426 |
|recommendation.image_section|323501  |
+----------------------------+--------+

spark.sql("""
select tag, count(*) from apizzata.image_suggestions_search_index_full
where snapshot='2026-03-16' group by tag""").show(truncate=False)

+----------------------------+--------+
|tag                         |count(1)|
+----------------------------+--------+
|recommendation.image        |4040426 |
|recommendation.image_section|323501  |
+----------------------------+--------+

spark.sql("""
select tag, count(*) from analytics_platform_eng.image_suggestions_search_index_delta
where snapshot='2026-03-16' group by tag""").show(truncate=False)

+----------------------------+--------+
|tag                         |count(1)|
+----------------------------+--------+
|recommendation.image        |4041911 |
|recommendation.image_section|378379  |
+----------------------------+--------+

spark.sql("""
select tag, count(*) from apizzata.image_suggestions_search_index_delta
where snapshot='2026-03-16' group by tag""").show(truncate=False)

+----------------------------+--------+
|tag                         |count(1)|
+----------------------------+--------+
|recommendation.image        |4041911 |
|recommendation.image_section|378379  |
+----------------------------+--------+

spark.sql(""" select tag, max(values), min(values) from apizzata.image_suggestions_search_index_full
where snapshot='2026-03-16' 
group by tag""").show(truncate=False)

+----------------------------+------------+------------+
|tag                         |max(values) |min(values) |
+----------------------------+------------+------------+
|recommendation.image        |[exists|990]|[exists|700]|
|recommendation.image_section|[exists|970]|[exists|710]|
+----------------------------+------------+------------+

spark.sql(""" select tag, max(values), min(values) from apizzata.image_suggestions_search_index_delta
where snapshot='2026-03-16' 
group by tag""").show(truncate=False)

+----------------------------+------------+---------------------+
|tag                         |max(values) |min(values)          |
+----------------------------+------------+---------------------+
|recommendation.image        |[exists|990]|[__DELETE_GROUPING__]|
|recommendation.image_section|[exists|970]|[__DELETE_GROUPING__]|
+----------------------------+------------+---------------------+

spark.sql(""" select tag, max(values), min(values) from apizzata.image_suggestions_search_index_delta
where snapshot='2026-03-16' and !array_contains(values,'__DELETE_GROUPING__')
group by tag""").show(truncate=False)

+----------------------------+------------+------------+
|tag                         |max(values) |min(values) |
+----------------------------+------------+------------+
|recommendation.image        |[exists|990]|[exists|700]|
|recommendation.image_section|[exists|970]|[exists|710]|
+----------------------------+------------+------------+

Tomorrow I will find the best way to delete the bad data from the tables and rerun everything

a-pizzata merged https://gitlab.wikimedia.org/repos/structured-data/image-suggestions-data-pipelines/-/merge_requests/9

add concatenate and exists

spark.sql("""
(
select * 
 from analytics_platform_eng.image_suggestions_search_index_delta where snapshot='2026-03-16'
 and tag = 'recommendation.image'
 limit 5)
 union all 
 (
select * 
 from analytics_platform_eng.image_suggestions_search_index_delta where snapshot='2026-03-16'
 and tag = 'recommendation.image_section'
 limit 5)
  """).show(truncate=False)

+-----------+--------------+-------+----------------------------+------------+----------+
|wikiid     |page_namespace|page_id|tag                         |values      |snapshot  |
+-----------+--------------+-------+----------------------------+------------+----------+
|aawikibooks|0             |1      |recommendation.image        |[exists|970]|2026-03-16|
|abwiki     |0             |2441   |recommendation.image        |[exists|980]|2026-03-16|
|abwiki     |0             |2443   |recommendation.image        |[exists|980]|2026-03-16|
|abwiki     |0             |2444   |recommendation.image        |[exists|980]|2026-03-16|
|abwiki     |0             |2445   |recommendation.image        |[exists|980]|2026-03-16|
|huwiki     |0             |1639080|recommendation.image_section|[exists|800]|2026-03-16|
|huwiki     |0             |1640392|recommendation.image_section|[exists|710]|2026-03-16|
|huwiki     |0             |1641209|recommendation.image_section|[exists|710]|2026-03-16|
|huwiki     |0             |1641486|recommendation.image_section|[exists|800]|2026-03-16|
|huwiki     |0             |1641865|recommendation.image_section|[exists|710]|2026-03-16|
+-----------+--------------+-------+----------------------------+------------+----------+


spark.sql("""
(
select * 
 from analytics_platform_eng.image_suggestions_search_index_full where snapshot='2026-03-16'
 and tag = 'recommendation.image'
 limit 5)
 union all 
 (
select * 
 from analytics_platform_eng.image_suggestions_search_index_full where snapshot='2026-03-16'
 and tag = 'recommendation.image_section'
 limit 5)
  """).show(truncate=False)

+--------------+--------------+-------+----------------------------+------------+----------+
|wikiid        |page_namespace|page_id|tag                         |values      |snapshot  |
+--------------+--------------+-------+----------------------------+------------+----------+
|cawiki        |0             |770438 |recommendation.image        |[exists|700]|2026-03-16|
|hywiki        |0             |770438 |recommendation.image        |[exists|800]|2026-03-16|
|zh_min_nanwiki|0             |770439 |recommendation.image        |[exists|980]|2026-03-16|
|simplewiki    |0             |770439 |recommendation.image        |[exists|800]|2026-03-16|
|simplewiki    |0             |770440 |recommendation.image        |[exists|800]|2026-03-16|
|lvwiki        |0             |1      |recommendation.image_section|[exists|710]|2026-03-16|
|swwiki        |0             |2      |recommendation.image_section|[exists|800]|2026-03-16|
|lbwiki        |0             |2      |recommendation.image_section|[exists|800]|2026-03-16|
|etwiki        |0             |2      |recommendation.image_section|[exists|800]|2026-03-16|
|dewiki        |0             |3      |recommendation.image_section|[exists|800]|2026-03-16|
+--------------+--------------+-------+----------------------------+------------+----------+

spark.sql("""
(
select * 
 from analytics_platform_eng.image_suggestions_search_index_delta where snapshot='2026-03-16' and array_contains(values,'__DELETE_GROUPING__')
 and tag = 'recommendation.image'
 limit 5)
 union all 
 (
select * 
 from analytics_platform_eng.image_suggestions_search_index_delta where snapshot='2026-03-16' and array_contains(values,'__DELETE_GROUPING__')
 and tag = 'recommendation.image_section'
 limit 5)
  """).show(truncate=False)

+-------+--------------+-------+----------------------------+---------------------+----------+
|wikiid |page_namespace|page_id|tag                         |values               |snapshot  |
+-------+--------------+-------+----------------------------+---------------------+----------+
|acewiki|0             |9587   |recommendation.image        |[__DELETE_GROUPING__]|2026-03-16|
|arwiki |0             |88243  |recommendation.image        |[__DELETE_GROUPING__]|2026-03-16|
|arwiki |0             |423129 |recommendation.image        |[__DELETE_GROUPING__]|2026-03-16|
|arwiki |0             |578188 |recommendation.image        |[__DELETE_GROUPING__]|2026-03-16|
|arwiki |0             |756871 |recommendation.image        |[__DELETE_GROUPING__]|2026-03-16|
|rowiki |0             |569548 |recommendation.image_section|[__DELETE_GROUPING__]|2026-03-16|
|rowiki |0             |573262 |recommendation.image_section|[__DELETE_GROUPING__]|2026-03-16|
|rowiki |0             |574800 |recommendation.image_section|[__DELETE_GROUPING__]|2026-03-16|
|rowiki |0             |576200 |recommendation.image_section|[__DELETE_GROUPING__]|2026-03-16|
|rowiki |0             |579720 |recommendation.image_section|[__DELETE_GROUPING__]|2026-03-16|
+-------+--------------+-------+----------------------------+---------------------+----------+

All looks good to me, @dcausse if you agree I will run the task publish_page_change_weighted_tags.

In T368987#11771834, @APizzata-WMF wrote:

All looks good to me, @dcausse if you agree I will run the task publish_page_change_weighted_tags.

Awesome, thanks! yes please feel to re-run this task

The task is running.

The task finished running during the night, @dcausse do the numbers look good now?

In T368987#11776496, @APizzata-WMF wrote:

The task finished running during the night, @dcausse do the numbers look good now?

yes all seem correct, we can now filter recommendations by scores hasrecommendation:image>0.98, thanks!

perfect! Will keep the ticket open for tomorrow run, if everything looks good I will close it.

@dcausse can you also confirm that the latest April run / data was successful? Thanks.

Ahoelzl edited projects, added Data-Engineering (Q4 FS25/26 April 1st - June 30st); removed Data-Engineering (Q3 FY25/26 January 1st - March 31th).Fri, Apr 3, 10:26 PM

Ahoelzl moved this task from Next Up to Ready to Deploy on the Data-Engineering (Q4 FS25/26 April 1st - June 30st) board.

@Ahoelzl yes I can confirm the run scheduled on April 2nd did run properly.

Ahoelzl moved this task from Ready to Deploy to Done on the Data-Engineering (Q4 FS25/26 April 1st - June 30st) board.Wed, Apr 8, 4:35 PM

Add an Image: filtering by suggestion "kind" or "confidence"Open, MediumPublicActions

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