I am building a (pivot) grid in Tableau and want to always include a data point (a row in the fetched dataset) in the resultant view, irrespective of any filters the user selects. Is this possible?
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I have a large text table (about 200k records) that's generated from a custom SQL query. I've added filters so users can limit the output, but the text table is still quite large, so rendering of the table is pretty slow. I know that I can limit the rows displayed using a calculated field like Index(). However, what if I want to limit the rows displayed to the user, but still enable them to pull the full dataset? In other words, lets say they filter by ID #123 and the text table has 5k records with ID #123. I want to display at most 100 of these records in the dashboard and if they need the complete raw data, they can pull the 5k into a crosstab. Currently, if I apply an Index to limit the rows displayed in the dashboard to 1k, they'll only be able to download 1k records to the dashboard.
Ultimately, the purpose is to make the raw data available, but make the experience using the dashboard a lot faster.
You could create a separate sheet purely for download. When downloading all of the records on the Detail shelf are exported - the fields don't need to be visible in the dashboard. Therefore you could create some form of dummy field - perhaps something simple like a SUM([Number of records]) - to display in the view with the remainder of the fields hidden on the Detail shelf. This means the view won't take an age to render but the fields will still export.
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.
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
I've built a geographic report for a new system that has very little data in it so far. The report combines two maps into one image with dual axis.
The first map shows different regions identified by color. It's supposed to always be visible, no matter what values are selected in a filter.
The second map shows business-related data, e.g., geographical locations of offices and number of applicants per office.
The data set is a union of business-related data and geographic data containing nulls in business-related columns.
The problem is that the nulls are showing in the filters, and this is confusing for the users. Basically, the nulls always need to be selected in order for the general map to be visible. If a user deselects NULL from any of the filters, the map disappears.
How can I fix it? Ideally, the NULLs (or a value replacing the null) should always be included in the data and be always excluded from the filter.
My SQL Table contains RmaNumber, RmaLineNumber and Warehouse, and then a whel lot of other details.
We want to filter (using a parameter) on warehouse to produce a list of RMANumbers and RMALinenumbers to choose from. The problem is that when I include the RmaLineNumbers it makes the dataset to large to display in Crystal Reports.
So I tried splittin the data into 2 tables - the first table contains the Warehouse and RMANumber. The second table contains the RmaNumber and RmaLine Number. The idea is that I put a parameter on the first table to select the warehouse and it returns a list of RMANumbers (a manageable size data set)Then the user will select which RMANumbers they want and from that list I want to filter (parameter) From the second table to see the line numbers (a smaller dataset) then the report will display the details based on the line number chosen. Is what I am trying to do possible in Crystal? is there another way around the issue of the dataset being to large?