Best Of
Re: Is there a equivalent Excel WORKDAY function in DOMO? Or is there any workaround way?
@Canioagain the formula shows up in the formula tile in Magic ETL. For whatever reason, the beast mode editor in Analyzer doesn't show as extensive list of functions, but 95% of the functions you see in the formula tile in Magic ETL will also work in the Beast Mode Analyzer.
Re: Multiple Event Types on a Calendar Card
Hi @Stuck, the default 'Calendar' chart doesn't allow more than one fields to be displayed, nor does it allow tooltips. As a result, there's a solution that I've outlined to layer multiple fields but using a custom svg chart route: https://www.domo.com/blog/devising-a-custom-calendar-with-tooltips/.
Let me know if there are any questions on that write-up.
amehdad
Re: What is the difference between Multi cloud and federated?
@vivekmani28 A "multi cloud" solution with Snowflake would mean that data is imported from Snowflake into Domo and the data is stored on your instance. The federated version of Snowflake is a connection to your Snowflake instance but the data isn't stored in Domo. Instead, whenever the data is needed (viewing a card with the data), Domo queries Snowflake and the data is sent to Domo to be visualized. One big drawback is you can't do any ETL's with federated datasets because the data isn't actually in Domo. Here's an article from Domo about federated data and the benefits and drawbacks:
Re: CONCAT function not working, any reasons?
Can you do the concat if you rename one of the columns in the data view?
Re: CONCAT function not working, any reasons?
Once you have your output dataset, that dataset is the table, so there's no way to reference the source table it comes from. If you've done the join in MagicETL, then you should have the option in the join tile to drop duplicate columns. Alternatively, you could just rename the duplicate columns.
Re: HELP with Case When Statement
Hi, @ST_-Superman-_ wow, this is awesome! Thank you so much for this. Will try this in ETL and let you know the feedback asap :D
Zel
Re: Splitting up multiple-value fields into multiple rows
If you know the possible values for each multi-select answer, you could create different calculated fields for each. Something like this:
`apple`
sum(case when `column 1` like '%apple%' then 1 else 0 end)
You would then do similar fields for cherry, banana, blue, red, green...
Then you can create a table card and drag these calculations into the columns section:
You can also use the "Transpose" option in the general chart properties to swap the columns and rows:
Re: HELP with Case When Statement
Hi @Zel
I used a filter tile to identify all alarm IDs that have both "Lost Connectivity" and "Disregard". I then left join that back to your original dataset after adding a column that says to exclude those IDs.
The resulting dataset looks like this:
Here is the JSON code that you can copy and paste into an ETL to mimic what I did.
{"contentType":"domo/dataflow-actions","data":[{"name":"@Zel Dojo","id":"6d9d3106-a084-481d-a69d-74840f17d018","type":"LoadFromVault","gui":{"x":36,"y":180,"color":3238043},"dependsOn":[],"removeByDefault":false,"notes":[],"dataSourceId":"864c1409-461e-46fc-b4b3-0ed644903782","executeFlowWhenUpdated":true,"onlyLoadNewVersions":false,"columnSettings":{},"visiblePartitionColumn":null,"versionWindow":null},{"name":"LostConnectivity and Disregard","id":"49f0cb44-56bb-4e19-ae8b-b83be193e3c6","type":"Filter","gui":{"x":144,"y":288},"dependsOn":["6d9d3106-a084-481d-a69d-74840f17d018"],"removeByDefault":false,"notes":[],"filterList":[{"leftField":"alarmDescription","rightValue":{"value":"Lost Connectivity","type":"STRING"},"operator":"EQ","andFilterList":[{"leftField":"alarmAction","rightValue":{"value":"Disregard","type":"STRING"},"operator":"EQ","andFilterList":[]}]}]},{"name":"Group By","id":"b8d8da16-2db0-4d88-9287-b349901d7d54","type":"GroupBy","gui":{"x":264,"y":288},"dependsOn":["49f0cb44-56bb-4e19-ae8b-b83be193e3c6"],"removeByDefault":false,"notes":[],"addLineNumber":false,"lineNumberFieldname":null,"giveBackRow":false,"allRows":false,"groups":[{"name":"alarmID"}],"partitionedAggregation":false,"fields":[{"name":"Count","source":"alarmID","type":"COUNT_ALL"}]},{"name":"Add Constants","id":"2c3aa4bb-07f5-45f4-abfa-26e9747f1fa5","type":"Constant","gui":{"x":372,"y":288},"dependsOn":["b8d8da16-2db0-4d88-9287-b349901d7d54"],"removeByDefault":false,"notes":[],"fields":[{"name":"FilterCriteria","type":"STRING","value":"exclude"}]},{"name":"Join Data","id":"e9e76a06-7a82-429a-bb3f-f1e912e1d6bc","type":"MergeJoin","gui":{"x":492,"y":180},"dependsOn":["6d9d3106-a084-481d-a69d-74840f17d018","2c3aa4bb-07f5-45f4-abfa-26e9747f1fa5"],"removeByDefault":false,"notes":[],"joinType":"LEFT OUTER","step1":"6d9d3106-a084-481d-a69d-74840f17d018","step2":"2c3aa4bb-07f5-45f4-abfa-26e9747f1fa5","keys1":["alarmID"],"keys2":["alarmID"],"schemaModification1":[],"schemaModification2":[{"name":"alarmID","rename":"","remove":true},{"name":"Count","rename":"","remove":true}],"partitioningInputId":""},{"name":"Add Formula","id":"9a80fd0d-33fb-4085-a20a-3ab856f5a762","type":"ExpressionEvaluator","gui":{"x":600,"y":180},"dependsOn":["e9e76a06-7a82-429a-bb3f-f1e912e1d6bc"],"removeByDefault":false,"notes":[],"expressions":[{"fieldName":"FilterCriteria","expression":"IFNULL(`FilterCriteria`,'include')","settings":null}]},{"name":"@Zel output","id":"f32d6203-2ab9-42b0-b44b-f0ee823202f3","type":"PublishToVault","gui":{"x":708,"y":180},"dependsOn":["9a80fd0d-33fb-4085-a20a-3ab856f5a762"],"removeByDefault":false,"notes":[],"dataSource":{"name":"@Zel output"},"partitionIdColumns":[],"upsertColumns":[]}]}