How can I list all the measures?

In Transform (https://transform.co/),

select * from mql_list_metrics()

How can I list all the measures in Holistics?

Welcome to the community Hyun Lee!

Just want to clarify the questions: can you share what you are trying to achieve (creating a report, writing a query…) at the moment in Holistics? What are the “measures” you mentioned?

can you share what you are trying to achieve (creating a report, writing a query…) at the moment in Holistics?

It doesn’t matter how it is.
I want to view table with 2 columns (metric, dimensions) like a captured image I attached.

What are the “measures” you mentioned?

measure of data model.

Unfortunately, Holistics doesn’t support this atm. However, if this is critical, I think you can request the support team to extract a CSV file of measures x dimensions. Anw, this is an interesting use-case, how would you use the list afterward?

how would you use the list afterward?

I want to guide company members to discover data in the right way.

I think “the right way” is :

[1] list all the metrics (with all the dimensions for each metric)
[2] find and select which metric to check.
[3] click that metric → linked to appropriate visualization (like holistics report)
[4] if necessary, check what sql is used.

for [4], if data model/dimension/measure are properly prepared, I think sql should be simple.

e.g.

select
{{ dimension1 }},
{{ sql expression for measure }}
from
{{ model }}
where
{{ dimension2 = ~~~}}
and {{ dimension3 = ~~~}}

group by
{{ dimension1 }}
order by
{{ dimension1 }}

I recognize that, this kind of concept is called “metrics store” these days.

e.g. https://transform.co/

and, I think it is also aligned with spirit of Holistics : “self-service” and “data modeling layer”

So, for [1], I asked this topic.

I see, thanks for the detailed explanation.

Since you are on version 2.7, I’m not sure if your team has been using datasets.

In Holistics 3.0 and above, we use datasets as containers of related data models, measures, and dimensions. Your team can these predefined datasets to explore data and create visualizations by selecting the measures (metrics) and dimensions. And for [4], your team can even check the underlying formula of the measures and dimensions.

Since you are on version 2.7, I’m not sure if your team has been using datasets.

yes, our team recognize [datasets], but now it’s not being used well. (our fault)

but anyway, I hope beginning of all the stories is [metrics], not [datasets].

The most important point here is you should have such data in your database (metric, dimension).

When you import the data into Holistics, you can use the datasets (with drag-and-drop interface) to generate the exact same table you want. Alternatively, you can write transform models based on the imported table to modify it as you want.

To link from that table to appropriate visualization in Holistics, we’d suggest using HTML in the metric column: Formatting Data | Holistics Docs

The most important point here is you should have such data in your database (metric, dimension).

I disagree.

With your approach,
if we want to define new single metric,
we have to do take care of “two different” things,

[1] define new measure in data modeling layer.
[2] insert/update the metric/dimension table you said.

It is vulnerable to human errors.
Because somebody can only care about one side and forget the other.

So, the ideal image that I have in mind is,
human only take care of [1],
and system generate metric/dimension table (logically or physically).

And that’s what metrics store like https://transform.co/ provides,
human define metric/dimension in yaml,
(fyi. Transform Metrics Framework | Transform Data)
and system generate some inferfaces.
(e.g. select * from mql_list_metrics() )