I have a problem with Power BI in the use of multiple direct active relationship between two table.
I have this 2 table: Population and Cost and I want to graph the the costs over the years in the different regions according to the population of the region.
In Population the attributes of my interest are: Year, Region, #Population, insted in Cost I have: Year, Region, Costs. So I need to create two active relationship between Year and Region in the two tables. However I can't do that in Power BI.
I tryed to generate a new Population table (an identical copy of the other) and create the two active relationship: the first (for Years) between Cost and one Population, the second (for Region) between Cost and the other Population.
Unfortunately this solution is not successful, in fact, by dividing the costs for the population, in one case I obtain the aggregation over all the years, in the other the aggregation of all regions.
Does anyone have any idea how to solve the problem?
Each Power BI relationship is limited to a single column from each table. The typical workaround to your scenario is to create a concatenated column on each table.
You can do this in the Query Editor (my preference) using the Merge Columns button from the Add Column ribbon.
The other method would be using the Add Column button (e.g. on the Modeling ribbon) and writing the DAX formula e.g.
Year Region Key = [Year] & [Region]
Once you have a concatenated column added to both tables, use that to create the active relationship.
Related
I have the following tables
I have several tables on coal consumption, natural gas, .....
I want to have a power BI model that can allow viewing these data with years (x-axis) while filtering on countries.
I have transposed the data to have a column with years and countries on the columns. But I cannot filter on countries.
Another thing I have done is to unpivot all the data and have four columns (country, year, value, fuel type) but the problem is that I could not manage to create suitable relationships between the tables as there is no primary key.
I have thought on putting all the data fro the different energy sources in one table. But how can I manage to link it to more data per country at year as well.
Another thing I have done is to unpivot all the data and have four columns (country, year, value, fuel type)
This is totally the right approach.
The next step required in minimum is to combine all unpivotted tables vertically into one EnergyConsumption table. You can utilize Append Queries command in Power Query Editor, or Table.Combine function in M language.
Additionally, you should consider to create three tables: Years, Countries, and FuelTypes, which have unique values of the respective dimensions, and establish one to many relationship with EnergyConsumption table.
I'm trying to create a column that has a total of values between 3 columns from 3 tables. How would I go about doing this?
The 2 tables are tables of values that share an id, and they are both linked to a table of account by Id. The goal is to add up 3 columns, and place it into a table grouped by the Id.
I've attempted summing them, trying to use the USERELATIONSHIP function, and creating a relationship between them. It seems to give very inaccurate results, as if it's summing all of the totals together, and passing them to each Id. That, or it won't let me use the column, as if it never existed.
EDIT: General Idea of what I'm trying to do (Lines should be pointing to Account's Id column, but I messed up the lines)
EDIT 2: I also forgot to illustrate or mention. There are more columns with information in each table that can't be summarized for each account preventing me from just merging the table together.
Make sure your data model looks like this (change names as you please, but the structure must be the same):
In dimensional modeling, your table "Account" is a Dimension, and both fee tables are Fact tables. The operation of combining data from multiple fact tables that share the same dimension is called "drill-across", and it's a standard functionality of Power BI.
To combine fees from these tables, you just need to use measures, not columns. This article explains the difference:
Calculated Columns and Measures in DAX
First, create 2 measures for the fees:
Fee1 Amount = SUM(Fee_1[Amount])
Fee2 Amount = SUM(Fee_2[Amount])
Then, create a third measure to combine them:
Total Fee Amount = [Fee1 Amount] + [Fee2 Amount]
Create matrix visual, and place Account_ID from the Account table on the rows. Then drop all these measures into the matrix values area, like this:
Result:
Of course, you don't have to have all these measure in the matrix, I just showed them for your convenience, to validate the results. If you remove them, the last measure still works:
I'm trying to figure out how to get a measure to adhere to the filter set by a slicer in Power BI.
My DAX query is: Block Time Cost = SUMX( FILTER(v_Invoice_Line_Items, v_Invoice_Line_Items[IV_Item_RecID]=9), v_Invoice_Line_Items[billable_ext_price_amount])
I know very, very little about DAX so my initial query may be way off base.
It calculates as I expect, but when filter with a date range silcer the value does not update as expected or at all.
I'm pulling my data from two views in the same database, v_Invoice and v_Data_Combined. I have a page level filter on the row Record_Description to limit the data to the types I'm looking for and the measure pulls it's data from rows in the v_Data_Combined view.
The rows in v_Invoice are below.
A sample copy is here.
and the rows for v_Data_Combined, if you click they will enlarge.
A sample copy is here.
I have no relations set between the views.
How can I have a measure adhere to slicer filters?
The slicer has to be on the same table as the measures you're filtering, or on a table related to that table. If your slicer is on a column in v_Invoice and your data is from v_Data_Combined - and the 2 tables are unrelated in Power BI, the slicer from one table will have no effect on the data from the other table.
Without sample data (which can be fake data), it's hard to make further recommendations.
However, if the two tables you have aren't really related to each other, then I would recommend exploring the possibility of "lookup" tables. E.g. if you have Company_Name in both tables, then you might add a 3rd table that is a unique list of companies (their name, address, etc). Then, when you want to slice by company you would slice on this 3rd table. That slicer will then filter both related tables (without having to have the tables related to each other).
You can read more about data modeling in Power BI, and how to design lookup tables, here: https://powerpivotpro.com/2016/02/data-modeling-power-pivot-power-bi/
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.
I'm attempting to create a shared date dimensions between two fact tables in Power BI, based off of a relational data source.
Currently, if I include an unrelated dimension in the report, I get numbers duplicated across multiple rows, where they don't really apply.
I'm wondering if there is any way to tell Power BI that certain dimensions cannot be used with certain fact tables, similar to using IgnoreUnrelatedDimensions in SSAS.
Currently the only solution I can find is to create a separate date dimension, so that the two fact tables have no relationship that could be used to join them, however this would mean forfeiting the ability to do any time based comparisons.
Create a combined view of the fact tables with only compatible columns to be used for time based comparison:
In Query Editor, create new queries for your fact tables by
referencing i.e. right click original query and select "Reference".
Then in those "copies" cut out the incompatible dimensions.
Rename columns to align terminology (e.g. Sales Date ==> Transaction Date, Payment Date ==> Transaction Date).
Use "Merge Queries" function to combine the copies using Full Outer Join.
Join this merged view to your date dimension