I have 6 tables and am creating 6 separate sheets of visuals per table. I want to have a measure that just shows a simple row count aggregate. For naming consistency, I want to create one measure named 'OLs' (order lines) that dynamically switches out based on the table selected (via visual tab selection or something similar).
I have been manually creating a measure in each table, but PBI doesn't allow different measures with the same name. The requirement is to have one consistent name.
I guess the other option is to create a column in each table's query using M, but I've heard that this method isn't recommended for aggregation.
OLs = COUNTROWS(Table1)
assuming you have the real calculations already created, here's what you should do.
Create new table with one column, which has the possible selections in it.
Then create new measure with desired name, which will do the logic.
measure_name = Switch (
True(),
SelectedValue(customTable[custom column] = "selection 1"), Metric A,
SelectedValue(customTable[custom column] = "selection 2"), Metric B,
...,
Blank()
)
After having a working measure, you put a slicer of the created selection column and force the single select. Users will be able to select desired calculation based on the slicer selection.
Workaround: create table union in M and then have just a single calculation.
Related
Imagine that I have a column with the following values: [A1,A2,A3,A4,T1,T2,T3]
Now, I have a slicer with the mentioned column, but I need that the the "Ts" (T1,T2 and T3) are always selected / filtered and when I choose a specific "A" (A1) for example, dosn't filter the "T".
For example:
If I select with the slicer "A1" the filter in the page should include: [A1,T1,T2,T3]
If I select "A2": [A2,T1,T2,T3]
So If I select an "A" it have to select the specific "A" and all the "Ts".
How can I do that? With filters? relationships?
Thanks
Short answer: we need a parameter table.
This because we might be able to write a measure that internally sets the filter according to our specification, but the Power BI visual would intercept the slicer setting first and would show only the selected rows or columns (for a matrix visual).
Assuming we have the table
this measure ignores any selection from the slicer, computing the total of the whole column, but the matrix visual will only show the row selected with the slicer
TotalV = SUMX(ALL(T), T[V] )
To solve this we can build a parameter table with the combination we want when selecting the F parameter, for instance like the following Parameter table
The column P is to be used in the slicer, while the column F is used to set up a bi-directional relationship with the original T table
Now we create the relationship
We create the measure
SumV = SUM(T[V])
setting the slicer over 'P' and a matrix with 'T[F]' on the rows and the measure '[SumV]' as value we obtain the desired behavior
Additional considerations:
the Parameter table can be generated manually or using a DAX
calculated table
to build a better model we might create a dimension for F
the bidirectional relationship in this configuration doesn't make
the model ambiguous, but we must pay attention when adding tables
and relationships to the model
Hi everyone, I have a chart which I need that the x value (Axis) changes by changing the slicer value (this slicer is the yellow one that has all the Dims (x values)) and it comes from DimList table. For example, at the moment the chart is totalfreight by custid, but I need if I check the empid from the yellow slicer the chart value changed to totalfreight by empid. This happens for all of the slicer values.
But I don't like bridge table or any method that has a bad effect on performance because the FactTable has a billion rows and I modeled it in SSAS, tabular model and has a live connection. Thanks in advance.
I assume you're referring to the approach that uses a bridge table described in this article. I agree that you may face some performance problems given the amount of data in your model.
First of all, you should try to see if there's some other Power BI frontend functionality that you can use directly in the report, without changing your data model. Perhaps you can use Power BI bookmarks, links or maybe a custom visual?
If not, there's another approach you can use in the data model, that does not rely on bridge tables. Disclaimer: I haven't tested this - there could be other performance issues involved.
Construct a new dimension table with all the members from your individual dimensions. Ie. create a union of all EmpIDs, CustIDs, etc. Make sure you indicate the type of ID in a separate column. The table should look like this:
DimensionId MemberId
categoryid 1
categoryid 2
categoryid 3
custid 1
custid 2
custid 3
...
Let's name this table 'All Dimensions'. The table should not have any relationships to other tables (this is similar to the Parameter Table pattern.
Change your measures to apply a virtual relationship whenever something is selected on the 'All Dimensions' table, to properly filter the fact table:
SUM('factSale'[Freight])
would become:
SWITCH(
SELECTEDVALUE('All Dimensions'[DimensionId]),
"categoryid", CALCULATE(SUM('factSale'[Freight]),
KEEPFILTERS(TREATAS(VALUES('All Dimensions'[MemberId]), 'factSale'[CategoryId])),
"custid", CALCULATE(SUM('factSale'[Freight]),
KEEPFILTERS(TREATAS(VALUES('All Dimensions'[MemberId]), 'factSale'[CustId])),
"empid", CALCULATE(SUM('factSale'[Freight]),
KEEPFILTERS(TREATAS(VALUES('All Dimensions'[MemberId]), 'factSale'[EmpId])),
// ... etc. for all dimensions ...
, // Fallback, when nothing is selected on 'All Dimensions'
IF(NOT ISFILTERED('All Dimensions'[MemberId]),
SUM('factSale'[Freight])
)
)
Put the [DimensionId] column into a slicer and use the [MemberId] column as the axis on your bar chart. Note that the chart will not show anything unless exactly one item has been filtered on the [DimensionId] slicer.
Explanation: The SWITCH statement determines if any selection has been made on the [DimensionId] column of the 'All Dimensions' table. In that case, a filter is applied to the fact table, depending on which dimension has been selected, using the TREATAS function. We're using KEEPFILTERS to make sure that any existing filters made directly on the individual dimensions are kept as-is.
In case no selection has been made on the [DimensionId] column, we want to fall back to the standard measure SUM('factSale'[Freight]) but since we don't want to repeat this measure for all items on the [MemberId] column, we use IF(NOT ISFILTERED( ... to make sure that we return only a blank value, if [MemberId] is currently used on the chart axis.
My scenario is this: SalesValue have been entered for multiple sessions namely Lunch, Breakfast, dinner which is grouped by SessionKey in numbers. The same SalesValue repeats at times for 2 or more sessions for a given production plan date, based on MenuKey, RawMaterialKey and IngSFKey.
I need to use DAX query in Power BI to remove duplicated SalesValue based on ProductionPlanDate and SessionKey for a particular MenuKey in a given date.
I have attached the screenshot of a sample value range of SalesValue containing duplicate values for the same date across different sessions for your reference. For example, rows 7 and 14 have the same ProductionPlanDate, SessionKey, MenuKey, and SalesValue.
So you have a table with one "Grain" and you want to change the "Grain" by using a subset of the columns. Specifically you want only rows with distinct columns ProductionPlanDate, SessionKey, MenuKey and SalesValue
To do this in a DAX query you would use
evaluate
summarize
( 'table name'
, 'table name'[ProductionPlanDate]
, 'table name'[SessionKey]
, 'table name'[MenuKey]
, 'table name'[SalesValue]
)
You could provide this to create a calculated table or provide it to each measure that needs to work with this coarser grained data set.
However as it seems you are in Power BI the more appropriate place to do this would be to create your coarser grained table using Power Query (via the Edit Queries section of Power BI).
This is better than doing it in DAX as DAX is more tuned to analytics where Power Query is tuned to data transformation - and you want to do data transformation.
You can either keep the table that you have now alongside the new modified or replace it accordingly.
option A will just change your incoming table to have the new coarse grain.
option B will keep your original table and have the new grained table alongside it. Note that this will mean any Power BI visuals that you have created will need to be "rewired" to use the new table.
To do the transform in Power Query, the steps for both options are
Go to the Edit Queries area on PowerBI
Select the columns that you want to create the new Grain (i.e. ProductionPlanDate, SessionKey, MenuKey and SalesValue) by holding ctrl and clicking the column headers of each column in turn.
Right click on the column header for one of the selected columns and select "Remove Duplicates"
If you want option B, simply first copy the existing table by using "Reference" then do the same thing as follows:
Find your existing table on the left Queries section, r-click and click Reference
Rename the new table something appropriate
Apply the transform steps to the new table as above
Click Close & Apply and rewire any existing visuals that you need to use the new table
If you find you don't need your old table you can R-click on it in Power Query again and uncheck "Enable Load" so that PowerBI will not see it anymore.
I’m new to Power BI. Currently facing similar issue explained below in my product development.
I have created power bi modle with below dimensions and facts from adventureworksDW.
Then I created a calculated table, which gives result as sum of sales group by ProductSubCategory and ProductCategory. Below is the DAX for the calculated table.
Now I want to create a new calculated table, which gives me TOPn ProductSubCategory based on the Total sales amount.
Below is the DAX to do this.
and model relationships looks like below.
I want this TOPn rows to be displayed based on filter condition on product category. Something like below.
This works fine when I hardcode the product category value in the DAX itself. But if I want to change this product category values from the slicer selection, then I didn’t get any results.
What you are asking for is not possible as Power BI is currently designed. Slicers cannot affect calculated tables. Calculated columns and calculated tables are evaluated once when the data is first loaded and are static until the data is refreshed.
However, you can get the table visual you want in a much simpler manner by writing the appropriate measure and putting that in the table instead of defining an entirely separate table.
TotalSales = SUM(FactInternetSales[SalesAmount])
The Top N filtering is available in the visual level filters settings.
You can simply use the SELECTEDVALUE function as shown below.
var __SelectedValue = SELECTEDVALUE('ProductSales'[EnglishProductCatogaryName])
return
Filter(
'ProductSales',
'ProductSales'[EnglishProductCatogaryName] = __SelectedValue
)
)
I have a FactLosses Table, and a DimAccumulation table. I have brought them into PowerBi and I have placed a slicer to choose which accumulation zones i am interested in.
Once the user has selected the zones, i want to perform a group by year on the losses and sum the losses into year buckets. But only on the data that applies to the zones the user picked.
I am using the following DAX code to do the group by like so...
Table = SUMMARIZECOLUMNS(FactForwardLookingAccumulation[Year], "Losses By Year", SUM(FactForwardLookingAccumulation[Net Loss Our Share Usd]))
The problem is the new table always produces the same result. i.e When i make changes to which accumulation perils should be included it makes no difference to the summation. (it is summing the entire table)
I'd like to use the slicer to filter the fact table and then have the DAX query run on the filtered list. Is this possible?
If you want these tables to be responsive to filters or slicers on your report, then you can't write these as calculated tables that show up under the Data tab since those are computed before any filtering happens.
To get what you want, you have to do everything inside of a measure, since those are what respond to slicers. If you're looking for the max loss year once the grouping and summing are completed, you can write a measure along these lines:
Year Max =
VAR CalculatedTable = SUMMARIZECOLUMNS(FactForwardLookingAccumulation[Year], "Losses By Year", SUM(FactForwardLookingAccumulation[Net Loss Our Share Usd]))
RETURN MAXX(CalculatedTable, [Losses By Year])
Writing it this way will allow the calculated table to respond to your slicers and filters.