It has been a long time that I use SQL Server Profiler to diagnose my data models in the Power BI Desktop. I wrote a blog post in June 2016 about connecting to the underlying Power BI Desktop model from different tools, including SQL Server Management Studio (SSMS), Excel and SQL Server Profiler. In this quick post, I share a pbitool.json file that you can use to register the SQL Server Profiler as an external tool. Read more about how to register an external tool here. This is quite handy as this way to use SQL Server Profiler to diagnose Power BI Desktop without needing to find the diagnostic port. As an external tool, the SQL Server Profiler automatically connects to the data model via the diagnostic port. You can download the sqlserverprofiler.pbitool.json file from here. After you download the file you can open it in a text editor to see or modify the JSON code. If you are using SSMS 18, then you do not even need to modify the file. If you use a different version, the only thing you have to change is the “path”.
This is the fourth one in the form of Quick Tips. Here is the scenario. One of my customers had a requirement to get data from a Stored Procedure from SQL Server. She required to pass the values from a Query Parameter back to SQL Server and get the results in Power BI.
The solution is somewhat easy. I created a simple stored procedure in AdventureWorksDW2019 as below:
CREATE PROCEDURE SP_Sales_by_Date
@date int
AS
BEGIN
SET NOCOUNT ON;
SELECT *
FROM [dbo].[FactInternetSales]
WHERE OrderDateKey >= @date
END
GO
In Power BI Desktop, get data from SQL Server, then:
Enter Server name
Enter Database name
Select Data Connectivity Mode
Expand the Advanced options
Type in a SQL statement to call the stored procedure like below:
exec SP_Sales_by_Date @date = 20140101
Click OK
Click Transform Data
Now we need to create a Query Parameter. In my sample I create a DateKey in Decimal Number data type:
I wrote some other posts on this topic in the past, you can find them here and here. In the first post I explain how to create “Time” dimension with time bands at minutes granularity. Then one of my customers required the “Time” dimension at seconds granularity which encouraged me to write the second blogpost. In the second blogpost though I didn’t do time bands, so here I am, writing the third post which is a variation of the second post supporting time bands of 5 min, 15 min, 30 min, 45 min and 60 min while the grain of the “Time” dimension is down to second. in this quick post I jump directly to the point and show you how to generate the “Time” dimension in three different ways, using T-SQL in SQL Server, using Power Query (M) and DAX. Here it is then:
Time Dimension at Second Grain with Power Query (M) Supporting Time Bands:
Copy/paste the code below in Query Editor’s Advanced Editor to generate Time dimension in Power Query:
let
Source = Table.FromList({1..86400}, Splitter.SplitByNothing()),
#"Renamed Columns" = Table.RenameColumns(Source,{{"Column1", "ID"}}),
#"Time Column Added" = Table.AddColumn(#"Renamed Columns", "Time", each Time.From(#datetime(1970,1,1,0,0,0) + #duration(0,0,0,[ID])), Time.Type),
#"Hour Added" = Table.AddColumn(#"Time Column Added", "Hour", each Time.Hour([Time]), Int64.Type),
#"Minute Added" = Table.AddColumn(#"Hour Added", "Minute", each Time.Minute([Time]), Int64.Type),
#"5 Min Band Added" = Table.AddColumn(#"Minute Added", "5 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/5) * 5) + 5, 0)), Time.Type),
#"15 Min Band Added" = Table.AddColumn(#"5 Min Band Added", "15 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/15) * 15) + 15, 0)), Time.Type),
#"30 Min Band Added" = Table.AddColumn(#"15 Min Band Added", "30 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/30) * 30) + 30, 0)), Time.Type),
#"45 Min Band Added" = Table.AddColumn(#"30 Min Band Added", "45 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/45) * 45) + 45, 0)), Time.Type),
#"60 Min Band Added" = Table.AddColumn(#"45 Min Band Added", "60 Min Band", each Time.From(#datetime(1970,1,1,Time.Hour([Time]),0,0) + #duration(0, 0, (Number.RoundDown(Time.Minute([Time])/60) * 60) + 60, 0)), Time.Type),
#"Removed Other Columns" = Table.SelectColumns(#"60 Min Band Added",{"Time", "Hour", "Minute", "5 Min Band", "15 Min Band", "30 Min Band", "45 Min Band", "60 Min Band"})
in
#"Removed Other Columns"
You can now export the data direct from Power BI Desktop using my tool, Power BI Exporter. Read more here.
In some of my old posts, which are the most popular ones, I explained how to Export data Power BI Desktop or Power BI Service data to different destinations like CSV, Excel and SQL Server. In this quick tip I explain a very easy way to export the model data as a whole to either CSV or SQL Server with DAX Studio.
Daniil from XXL BI well explained this method, but I’d rather quickly explain how it works and add some more information.
After release 2.8 of DAX Studio, you can now quickly export the whole model to CSV and SQL Server in one shot.
