I am not sure how to model this.
I have 3 tables.
Fact
Contract
Clients
Fact:
Then, the access with RLS will be based on contract. If you are manager1 or manager2 for that contract you shall see it (also if you are c. manager1 on that row you shall see it too).
So, for the table for access, I will do an Unpivot like:
SqlTable
I have tried this model but it doesnt work:
Is there a way to achieve this functionality?
To make your life easy using RLS always try to create a simple "data entitlement" table with one column for the key value of the table you're trying to filter, and one column for the user id, here
ContractId UserId
1 Peter
1 Rob
2 Peter
2 Tim
. . .
Then set your RLS Dax filter on this table's UserId table using USERPRINCIPALNAME, and make sure it has a relationship that flows filters to the target table.
Related
I've imported three tables into Power BI using a REST API, have added relationships between them, and am now trying to add fields from the various tables to a table on the canvas. The table names (from a Human Resources database) are named Employees, Job History, and Salary History.
Employees is joined to Job History using EmployeeID as a 1:Many relationship, and also to Salary History using EmployeeID on a 1:Many relationship.
I can add fields from the Employee table and EITHER the Salary History OR the Job History table to the table on the report canvas. However, if I try to add fields from all three tables, I'm seeing the error 'Can't display the data because Power BI can't determine the relationship between two or more fields'.
Could anyone advise where I'm going wrong? Many thanks.
If I understand correctly, you have a model like in this picture:
The way PBI filters work is: The 1: side table filters the N: side table. Filters propagate that way. So in this case, you can filter JobHistory with data from Employees, and SalaryHistory with data from Employees. But the 2 fact tables can't relate because the filters don't propagate that way.
Look into DAX measures like RELATED(), RELATEDTABLE() and USERELATIONSHIP() that might work for you.
Without that, I don't think you can use data from the 3 tables, since you have a model with 2 Fact Tables.
Someone correct me if I'm wrong.
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
In Power BI, I am creating a report with some finance data of a company. I have 3 different tables. The table structure of all three tables are as follows:
I want to change these tables into this structure:
Is it possible to achieve this kind of structure? If yes and please suggest some method to do this?
To do it simply you can import 3 times your table using the query editor, and then in one table keep only columns for Planned, in the second table keep columns for Actual, and so on...
Hope that helps!
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.