I have two data sources in Google cloud storage buckets. I am blending them in Google data studio as follows:
I have created a simple table chart which is working fine:
But when I set Comparison date range option to Previous period, the cost numbers displayed in the same table go haywire but the summary row which displays the total cost is fine. I don't observe this issue if the data is not blended.
When you enable "Comparison data range" it only show comparable data (that means, data that can be comparable with something).
Since your data source probably contains rows of a dates that doesn't have a relative row to compare with (the previous period), that data is filtered out from your visualization.
Related
I am having trouble showing the correct totals in my tableau worksheet.
I have supervisors that are part of specific zones that need to complete a certain number of tests in different categories. For example, supervisor 15716 must complete 8 tests in category 1. I need to show the target, which is a number stored in the database and show the actual number of tests in that category that have been completed within a date range. I have it working, but Im not sure if I did it correctly because I can not show any totals.
System target - number stored in database
CountOfSheetID - calculated field
Percent Compliant - calculated field
Try this approach -
First define a calculated field called [Within Date Range?] as
[Date] >= [MyStartDate] AND [Date] <= [LastSelectedDayOfMonth]
and put that new field on the filter shelf, only including data where [Within Date Range?] is True. (You could also just filter the [Date] field if that is flexible enough for you)
The you don't need the CountofSheetId calculated field at all. If you want to know how many records have a non-null value for [SheetID] within your date range, you can simply drop [SheetID] on a shelf and choose to treat it as Measure with the aggregation function COUNT()
Then just build your visualization to show the counts you want (not percentages, the actual counts)
Finally, you can convert counts into Percentages by clicking on the pills for your Measures and choosing Percentage under Quick Table Calcs. You'll want to experiment with the "Compute Using" setting to tell Tableau how to compute your percentages -- i.e. define percentage of "what".
Percentages are implemented as table calcs in Tableau. Read the help to understand table calcs, especially the description of partitioning and addressing.
Gif of problem
I am currently working on a dashboard in tableau, which shows the count of New-User-Signups and Interactions side-by-side given different date windows. The first New-User-Signup happened before the first Interaction, and the last Interaction happened after the last User Signup.
In order to choose a date window, I linked the date fields in both data sources, and made a date filter, which I applied to all worksheets using related data sources.
However, depending on which "date" field I choose, (from the User Signup table or the Interaction table), the "All Dates" option of the date filter only goes from start to end of that data source's date range.
No matter what I try, I exclude some entries in either one graph or the other. How can I make the "All Dates" filter go from the minimum first date between both data sources, to the maximum last date between the two data sources?
I run into this issue a lot with the data that I use. The problem is that the filter will only be able to contain dates that are in the dataset it is created off of, even if you link the data sources. When I run into this issue, I use parameters instead.
You can find instructions here:
https://kb.tableau.com/articles/howto/creating-a-filter-for-start-and-end-dates-parameters
I have a calculation and it outputs multiple values. Then I am creating a table on those values. For example, in below data my formula is
if data is 1 then calculation is `one`
if data is 2 then calculation is `two`
if data is 3 then calculation is `three`
as three doesn't really appear in the output, when I create a table, three is not displayed. Is there any way to display it?
I tried table layout >> show empty rows and columns and it didn't work
data calculation
1 one
2 two
Tableau discovers the possible values for a dimension field dynamically from the query results.
If ‘three’ does not appear in your data, then how do you expect Tableau to know to make a column header for that non existent, but potential, value? It can’t read your mind.
This situation does occur often though - perhaps you want row or column headers to remain stable, even when you change filters in a way that causes some to no longer appear in the query results.
There are a few ways you can force Tableau to pad ** or **complete a domain:
one solution is to pad your data to make sure each value for your dimension field appears in at least one data row.
You can often do this easily by using a union to append some extra rows to your original data. You can often add padding rows that don’t impact any results by leaving all your Measure columns null since nulls are ignored by aggregation functions
Another common solution that is a bit more effort is to make what is known as scaffolding data source that is not much more than a list of your dimension members. You can then use that data source as a primary data source with data blending, making your original data source secondary.
There are two situations where Tableau can detect the absence of data and leave space for it in the visualization automatically
for numeric types, you can create a bin field that will automatically pad for missing bins
similarly, date fields can show missing values because, like bins, Tableau can tell when a month doesn’t appear in the data and leave room for it in the view
The documentation states (the words in brackets are mine):
[A time wizard dimension] allows us to define/generate a time
dimension without any underlying data table.
The accompanying image in the documentation does not show a field for entering a data table. However, when I look at the definition of the Time dimension in the demo Sales cube (version 6.5 of icCube), I see that a data table is in fact used. Also, there is no option in the drop-down menu to not specify a table. So, it becomes not clear what is special about the time dimension. What am I missing?
In icCube there is nothing really special about a "time" dimension.
However, you can define a time dimension as any other dimension using a table or using the "time wizard" that is going to generate days between the specified from and to dates (therefore no need of table).
The demo Sales schema is defining a time dimension using a table.
In its definition, a dimension is flagged as time (and possibly default time dimension) because it can be used as the default rollup hierarchy with custom aggregation (e.g., open non empty).
Note that several MDX functions (e.g., parallelPeriod, dtXyz) allows for navigating a time dimension in quite a specific way.
I have a table in BigQuery that has 35 million rows that I want to turn into a Tableau extract, but the number of rows is so great that it can't add all of them at one time. The solution I have come up with is to first the number of rows that are presented by the BigQuery view by only showing rows within a particular date range for a full extract and then after the extract is completed slowly increase the number of rows displayed by the view (by altering the where statement to only show particular rows) and then having Tableau perform an incremental extract based on the field containing the time stamp. That worked for a few of the incremental updates, but now I've run into a problem where Tableau Desktop says 'Required columns are not present in the remote data source. Perform full refresh of the extract', except that nothing in the data source or within tableau has changed other than the WHERE clause affecting the range of dates that the view presents. This was apparently a problem in Tableau 8, but I'm on Tableau 9.3. Anyone have any suggestions?
I'm not sure if this will be a solution for everyone, but the problem that I was having seems to have been caused by making connections to Google BigQuery per hour.