I have the tables as per the below diagram
There are vouchers in LedgerTrans connected with other 3 tables (but each one is independent of other 2 tables - means a voucher will be available in one of the 3 tables - same voucher won't be available across the 3 Project Trans tables).
I have given the connection as per below and the values are populating in 3 different Matrix visuals for each ProjTrans. The problem I am facing is, all the 3 visuals are summing up to the same amount, though the vouchers are showing correctly in each visual respectively. Is my approach wrong (the connection type)?
The 2nd problem is, I brought in the Project table to keep it as a slicer. The same project could be available in all the 3 ProjTrans. But when I select a project in the slicer, only the table with active connection is getting filtered out. The other 2 matrices are showing blank.
How to achieve active connections for all the 3 ProjTrans tables with a single Project table since Power BI would not allow more than 1 active connection?
The problem here isn't that Power BI does not allow more than one active connection. What is not allowed is having multiple paths for one table to filter another table since this results in ambiguities. Since you have bidirectional many-to-many relationships from the fProject tables to the fLedgerTrans table, you would have three distinct paths from dProject to fLedgerTrans if all your relationships were active.
The quickest fix would be to make all of the many-to-many relationships filter only in one direction (fLedgerTrans filters fProject tables). Then you should be able to activate the currently inactive relationships.
More generally, bidirectional many-to-many relationships are considered bad practice. I'd recommend reading the following article, especially if you don't quite understand what I've explained above:
Bidirectional relationships and ambiguity in DAX
Related
In my table primary key column have missing value, i have tried to fill using measure but it is not work because not full fill the primary key val of column to measure
For handling missing values, you need to follow the following two steps:
Replace the missing values with the desired values in Query Editor in Power BI Desktop (optional)
Remove the bi-directional relationships and create uni-directional relationships among tables
Note: The direction of the relationship plays a very important role in modeling in Power BI. The direction of the relationship means the way that filter propagates in Power BI. The uni-directional relationship will filter one table based on the other one. Sometimes you need to filter in a different direction, that is when the bi-directional relationship comes into play. However, bidirectional relationship comes with a cost of performance issues. Do not use bi-directional relationships blindly. Make sure you have designed your model in the right way first, and if that doesn’t work, then try other methods such as Cross-Filter DAX functions.
I have created static table as blow and create relationship with original tables then assigned value static table column on visual table which is working with out any issue
Create Static stable:
create relationship
assign column to visual table and filter result column should not be empty
I have the following scenario.
I have two fact tables [FactA and FactB]. FactA and FactB contains 9 common dimensions and their own measures. I am trying to pull the measures from both fact tables into a table visualization and trying to filter the results using common dimensions. It works for the measure pulled from one fact table and not for the other fact table. I tried to set the cross filter direction to both on all the relationships between common dimensions and facts. I was able to set the cross filter for one dimension table, when I am trying to set the same for remaining dimensions, I am getting an warning that Power BI desktop allows only one filtering path between tables in a data model.
Also I tried to see if the cross filtering is working fine for the one dimension that I enabled cross filtering by pulling that dimension key and measures from both facts. But it didn't change anything.
Is there a way I can pull measures from both facts and have it filtered by common dimension values? Please share your thoughts and suggestion. Thanks in advance.
I have joined all the dimension tables to both fact tables. All dimension tables have 1 to many relationships with Fact tables. I have hidden all the dimension columns in report view for both fact tables. I just have measures visible on both Facts. In the visualization tab, I have pulled the measures from fact tables and dimension columns from dimension tables. It fixed the issue.
Also I learnt that, you can derive a new measure using other measures available in different fact tables.
i have created Power bi project, It is working fine in the beginning but when i refresh my datasource , i get this error " not allowed for columns on the one side of a many-to-one relationship" . Any can help me ??
I resolved this issue by going into the relationship, right clicking to view properties,
and making it a Many to One Relationship.
Power BI sometimes automatically creates relationships between the queries that are being used to drive the data in the reports. When I have encountered this error or errors like it in the past I:
Go into Manage Relationships
Verify that there is a relationship listed
Evaluate the From and To relationships that are listed as active
Delete any invalid From and To relationships between separate data sets
My most common issue in the past has been that I will have two very different queries pulling data from separate sources with similar column names and Power BI will generate a relationship between them that is invalid. After removing the relationship it has always resolved my issue.
In my case issue was related to the fact that Power BI was threating "SQL View" as a "Table" and as a result it was creating relations for it.
Although I've checked the "Manage Relationships":
and removed one relation which was not reasonable the issue was still persisting.
Then issue solved when I had looked in the "Relations"
tab and found unreasonable relations related to my View and removed them.
None of these answers helped me. For me I received this error when trying to refresh my dataset which had previously worked for some time. After investigating I found the schema of the source database had changed. Two fields that previously didn't allow nulls now allowed nulls and had null values for some rows. My Power BI model still expected these fields not to contain nulls but was throwing this same and very misleading error:
Data source error: Column 'x' in Table 'y' contains blank values and this is not allowed for columns on the one side of a many-to-one relationship or for columns that are used as the primary key of a table. Table: y.
Initially on seeing this error and opening up my report in PowerBI Desktop and going to Modeling > Manage relationships. I looked for a relationship on table y for column x, but no such relationship existed!? Was I confused? You bet.
After investigating further I discovered the database schema change and resolved by updating my Power BI model by going to the data model editor, expanding table y in the Fields panel on the right hand side, selected field x, expanded "Advanced" in the Properties panel and changed "Is nullable" from No to Yes. I then applied the changes, saved the report and refreshed the dataset.
I followed these steps
Step 1: Go to the Model section from the left side of the Power BI Desktop
Step 2: Delete all the relationships (or connections) amongst the tables that have been created by Power BI itself while you were working with the Power Query Editor
Step 3: Click 'Refresh visual and data' option in Home (besides the Transform Data button)
It worked and loaded the new data and also applied the automations done in the query editor.
I got this error on a completely new table made in Power Query, weird since I had no chance to create a relation yet.
Easy fix: Apply a filter that removes all blanks on that column - apply the filter, and then delete this new filter again
Another problem you might have is that "Autodetect new relationships" is turned on:
This is a setting that disables auto-detecting relations under "File/Options & settings/Options/Current File/Data Load/Relationship/Autodetect new relationships after data is loaded"
I had the same issue, after spending hours of searching for a fix and not finding anything, I started scratching around and found the problem took 1second to fix. My issue specifically, was a an additional relationship created within the model. The connection showed up as a "dotted" line one of my tables. I deleted the relationship, refreshed. Done.
This happens when your table or connected tables in excel, contain blank row, for resolving this issue you will need to click anywhere in the excel table, then click on the table tools, then resize table and Select the entire range of cells to include all rows, make sure no blank rows are included then save and get back to your PowerBI then again refresh it, all will work.
I have created a powerpivot model include in the image below. I am trying to include the "IncurredLoss" value and have it sliced by time. Written Premium is in the fact table and is displaying correctly. I am aiming for IncurredLoss to display in a similar fashion
I have tried the following solutions:
Add new related column: Related(LossSummary[IncurredLoss]). Result: No data
DAX Summary Measure: =CALCULATE(SUM(LossSummary[IncurredLoss])). Result: Sum of everything in LossSummary[IncurredLoss] (not time sliced)
Simply adding the Incurred Loss column to the Pivot Table panel. Result: Sum of everything in LossSummary[IncurredLoss] (not time sliced)
A few other notes:
LossKey joins LossSummary to PolicyPremiumFact
Reportdate joins PolicyPremiumFact to the Calendar.
There is 1 row in LossSummary per date and Policy. LossKey contains this information and is the PK on that table.
Any ideas, clarifications or pointers are most certainly welcome. Thank you!
The related column should work. I was able to get it to work in both Excel 2016 and Power BI Desktop. Rather than bombarding you with questions, I'll try and walk through how I would troubleshoot further, in the hopes it gets you to a solution faster:
First, check the PolicyPremiumFact table inside Power Pivot and see if the IncurredLossRelated field is blank or not. If it is consistently blank, then the related column isn't working. The primary reason the related column wouldn't work is if there's a problem with your relationships. Things I would check:
Ensure that the relationships are between the fields you think they are between (i.e. you didn't accidentally join LossKey in one table to a different field in the other table)
Ensure that the joined fields contain the same data (i.e. you didn't call a field LossKey, but in fact, it isn't the LossKey at all)
Ensure that the joined fields are the same data type in Power Pivot (this is most common with dates: e.g. joining a text field that looks like a date to an actual date field may work, but not act as expected)
If none of the above are the problem, it doesn't hurt to walk through your data for a given date in Power Pivot. E.g. filter your PolicyPremiumFact table to a specific date and look at the LossKeys. Then go the LossSummary table and filter to those LossKeys. Stepping through like this might reveal an oversight (e.g. maybe the LossKeys weren't fully loaded into your model).
If none of the above reveals anything, or if the related column is not blank inside Power Pivot, my suggestion would be to try a newer version of Excel (e.g. Excel 2016), or the most recent version of Power BI Desktop.
If the issue still occurs in the most recent version of Excel/Power BI Desktop, then there's something else going on with your data model that's impacting the RELATED calculation. If that's the case, it would be very helpful if you could mock up your file with sample data that reproduces the problem and share it.
One final suggestion I have is to consider restructuring your tables before they arrive in your data model. In your case, I'd recommend restructuring PolicyPremiumFact to include all the facts from LossSummary, rather than having a separate table joined to your primary fact table. This is what you're doing with the RELATED field to some extent, but it's cleaner to do before or as your data is imported into Power Pivot (e.g. using SQL or Power Query) rather than in DAX.
Hope some of this helps.
I have two tables from Azure SQL in PowerBI, using direct query:
EMP(empID PK)
contactInfo(contactID PK, empID FK, contactDetail)
which have an obvious one-to-many relationship from EMP.empID to contactInfo.empID. The foreign key constraint is successfully enforced.
However I can only create a many-to-one relationship (contactInfo.empID to EMP.empID) in PowerBI. If I ever try the opposite, PowerBI always automatically converts the relationship to many-to-one (by swapping the from and to column), which prevents me from creating visuals. Does PowerBI think the two are equivalent?
Update:
What I'm doing is to just create a table in PowerBI showing the join results of these two tables. The foreign key constraint is contactInfo.empID REFERENCES EMP.empID, which is many-to-one. That should not be a problem, I guess, since I can directly query the join using SQL.
Please also suggest if I should create the foreign key in the opposite direction.
More info on failure to create visual
The exact error message is:
Can't display the data because Power BI can't determine
the relationship between two or more fields.
Version: 2.43.4647.541 (PBIDesktop)
To reproduce the error:
DB schema is as follows:
What I want is a table in PowerBI showing contact and sales info of am employee, that is, joining all the four tables. The error will occur when VALUES of the table visual contains "empName, contactDetail, contactType, productName", however, error will NOT occur if I only include "empName, contactDetail, contactType" or "empName, productName". At first I thought the problem may lie in the relationship between contactInfo and emp, but it now seems to be more complicated. I guess it may be caused by multiple one-to-many relationships?
Expanding my comments to make an answer:
Root of the Problem
In your data model, a single employee can have multiple contacts and multiple sales. But, there's no way for Power BI to know which contactDetail corresponds to which productName, or vice versa (which it needs to know to display them together in a table).
Deeper Explanation
Let's say you have 1 emp row, that joins to 10 rows in the sales table, and 13 rows in the contactInfo table. In SQL, if you start from the emp row and outer join to the other 2 tables, you'll get back (1*10)*(1*13) rows (130 rows in total). Each row in the contactInfo table is repeated for each row in the sales table.
That repetition can be a problem if you do something like sum the sales and don't realize a single sales record is repeated 13 times but might be fine otherwise (e.g. if you just want a list of sales and all associated contacts).
Power BI vs. SQL
Power BI works slightly differently. Power BI is designed primarily to aggregate numbers, and then break them down by different attributes. E.g. sales by product. Sales by contact. Sales by day. In order to do this, Power BI needs to know 100% how to divide numbers up between the attributes on your table.
At this point, I'll note that your database diagram doesn't include any obvious metrics that you'd use Power BI to aggregate. However, Power BI doesn't know that. It behaves the same whether you have metrics to aggregate or not. (And failing all else, Power BI can always count your rows to make a metric.)
Let's say that you have a metric on your sales table called Amt Sold. If you bring in the empName, productName, and Amt Sold columns, Power BI will know exactly how to divide up Amt Sold between empName and ProductName. There's no problem.
Now add in contactDetail. Using your database diagram, Power BI has no way of knowing how an Amt Sold metric in the sales table relates to a given contactDetail. It might know that $100 belongs to empID 27. And that empID 27 corresponds to 3 records in the contactInfo table. But it has no way of knowing how to divide up the $100 between those 3 contacts.
In SQL, what you'd get is 3 contacts, each showing the $100 amount sold. But in Power BI, that would imply $300 was sold, which isn't the case. Even equally dividing the $100 up would be misleading. What if the $100 belonged entirely to 1 contact? So instead, Power BI shows the error you're seeing.
My Recommendations
If you can, I recommend changing your data model before your bring it in. Power BI works best with a single fact table, which would contain your metrics (like amount sold). You then join this fact table to as many lookup tables as you like (e.g. customer, product, etc.), directly. This allows you to slice & dice your metrics with any combination of attributes from any of the lookup tables. I would recommend checking out the star schema data model and the concept of lookup tables: powerpivotpro.com/2016/02/data-modeling-power-pivot-power-bi
At the very least, you would want to flatten your tables (i.e. merge the contactInfo and sales tables into a single table before importing them into your data model.
It may be that Power BI isn't the best tool for what you're trying to accomplish. If all you want is a table showing all sales & contact info for an employee, without any associated metrics, a regular reporting tool + SQL query might be a better way to go.
Side Note: You can't reverse a many:one relationship to get past this error. The emp table contains one row per empID. Both the contactInfo and sales tables contain multiple rows with the same empID. This means the emp table is necessarily the "one" side of the relationship to both those tables. You can't arbitrarily change that.