Posted on by Debbie E

Power BI Dev to Prod without using Deployment Pipelines

Power BI Pipelines are a Premium Service which allows you to set up a development, QA and Production workspace and easily send your development changes across to the workspaces.

Each workspace can also be configured to work with different data sources. for example, your Dev Power BI may sit on top of test data, rather than the production data.

Because this is only available in Premium, we wanted to look into how difficult this process is outside of the Premium capacity.

Setting up the Development database

I wanted a poc development database for Power BI to work with. I’ve chosen household pets, with a bit of a surprise in Production.

the database was added to our POC server in Azure

Create Schema dim;
Create Schema fact;
Create table dim.Area (
AreaKey [int] IDENTITY(1,1) NOT NULL,
AreaDescription varchar (255)
);
CREATE TABLE [dim].[Pet](
[PetKey] [int] IDENTITY(1,1) NOT NULL,
[PetDescription] varchar NULL
) ON [PRIMARY]
;
CREATE TABLE [fact].[Petmetrics](
[AreaKey] [int] NOT NULL,
[PetKey] [int] NULL,
[PopulationwithPetsPerct] [int] NOT NULL,
[HouseholdswithPets000s] [int] NOT NULL,
[Petsperhousehold] [numeric](2, 1) NOT NULL,
[Petsperregion000s] [int] NOT NULL
) ON [PRIMARY]
;
Insert into dim.Area (AreaDescription)
SELECT 'North East' UNION
SELECT 'North West'UNION
SELECT 'Yorks and Humb'UNION
SELECT 'East Midlands' UNION
SELECT 'West Midlands' UNION
SELECT 'East'UNION
SELECT 'London' UNION
SELECT 'South East' UNION
SELECT 'South West' UNION
SELECT 'Wales' UNION
SELECT 'Scotland' UNION
SELECT 'Northern Ireland' UNION
SELECT 'UK' ;
Insert into dim.Pet (PetDescription)
SELECT 'cat' UNION
SELECT 'Dog';
WITH CTE_DOGS (AreaDescr, PopulationwithPetsPerct,HouseholdswithPets000s,Petsperhousehold,Petsperregion000s)
AS
(SELECT 'North East', 33 , 425, 1.3, 544 UNION
SELECT 'North West', 27, 825, 1.3, 1053 UNION
SELECT 'Yorks and Humb', 22, 545, 1.4, 773 UNION
SELECT 'East Midlands', 31, 750, 1.5, 1111 UNION
SELECT 'West Midlands', 28, 635, 1.3, 803 UNION
SELECT 'East', 21, 585, 1.4, 810 UNION
SELECT 'London', 92, 312, 1.1, 340 UNION
SELECT 'South East', 25, 950, 1.4, 1320 UNION
SELECT 'South West', 28, 674, 1.4, 940 UNION
SELECT 'Wales', 30, 460, 1.4, 647 UNION
SELECT 'Scotland', 23, 547, 1.5, 820 UNION
SELECT 'Northern Ireland', 40, 302, 1.4, 430 UNION
SELECT 'UK', 26, 6604, 1.4, 9000 )
INSERT INTO [fact].Petmetrics
SELECT a.AreaKey, (SELECT PetKey FROM dim.Pet Where PetDescription = 'Dog') AS PetKey,
d.PopulationwithPetsPerct,d.HouseholdswithPets000s,d.Petsperhousehold,d.Petsperregion000s
FROM CTE_DOGS d
INNER JOIN dim.Area a ON d.AreaDescr = AreaDescription
WITH CTE_CATS (AreaDescr, PopulationwithPetsPerct,HouseholdswithPets000s,Petsperhousehold,Petsperregion000s)
AS
(SELECT 'North East', 14, 195, 1.5, 286 UNION
SELECT 'North West', 16, 520, 1.6, 795 UNION
SELECT 'Yorks and Humb', 19, 443, 1.6, 680 UNION
SELECT 'East Midlands', 20, 480, 1.8, 854 UNION
SELECT 'West Midlands', 17, 400, 1.7, 662 UNION
SELECT 'East', 20, 512, 1.8, 876 UNION
SELECT 'London', 14, 428, 1.5, 580 UNION
SELECT 'South East', 20, 890, 1.8, 1422 UNION
SELECT 'South West', 21, 514, 1.6, 810 UNION
SELECT 'Wales', 22, 360, 1.7, 596 UNION
SELECT 'Scotland', 15, 381, 1.6, 590 UNION
SELECT 'Northern Ireland', 14, 106, 1.5, 160 UNION
SELECT 'UK', 18, 4995, 1.6, 8000)
INSERT INTO [fact].Petmetrics
SELECT a.AreaKey, (SELECT PetKey FROM dim.Pet Where PetDescription = 'Cat') AS PetKey,
d.PopulationwithPetsPerct,d.HouseholdswithPets000s,d.Petsperhousehold,d.Petsperregion000s
FROM CTE_CATS d
INNER JOIN dim.Area a ON d.AreaDescr = AreaDescription

Setting up the Production database

For this example the Production database is on the same server but it is likely to be on a different server. Not only that but a different Subscription in Azure

Create Schema dim;
Create Schema fact;
Create table dim.Area (
AreaKey [int] IDENTITY(1,1) NOT NULL,
AreaDescription varchar (255)
);
CREATE TABLE [dim].[Pet](
[PetKey] [int] IDENTITY(1,1) NOT NULL,
[PetDescription] varchar NULL
) ON [PRIMARY];
CREATE TABLE [fact].[Petmetrics](
[AreaKey] [int] NOT NULL,
[PetKey] [int] NULL,
[PopulationwithPetsPerct] [int] NOT NULL,
[HouseholdswithPets000s] [int] NOT NULL,
[Petsperhousehold] [numeric](2, 1) NOT NULL,
[Petsperregion000s] [int] NOT NULL
) ON [PRIMARY];
Insert into dim.Area (AreaDescription)
SELECT 'North East' UNION
SELECT 'North West'UNION
SELECT 'Yorks and Humb'UNION
SELECT 'East Midlands' UNION
SELECT 'West Midlands' UNION
SELECT 'East'UNION
SELECT 'London' UNION
SELECT 'South East' UNION
SELECT 'South West' UNION
SELECT 'Wales' UNION
SELECT 'Scotland' UNION
SELECT 'Northern Ireland' UNION
SELECT 'UK' ;
Insert into dim.Pet (PetDescription)
SELECT 'Lion' UNION
SELECT 'Wolf';
WITH CTE_DOGS (AreaDescr, PopulationwithPetsPerct,HouseholdswithPets000s,Petsperhousehold,Petsperregion000s)
AS
(SELECT 'North East', 33 , 425, 1.3, 544 UNION
SELECT 'North West', 27, 825, 1.3, 1053 UNION
SELECT 'Yorks and Humb', 22, 545, 1.4, 773 UNION
SELECT 'East Midlands', 31, 750, 1.5, 1111 UNION
SELECT 'West Midlands', 28, 635, 1.3, 803 UNION
SELECT 'East', 21, 585, 1.4, 810 UNION
SELECT 'London', 92, 312, 1.1, 340 UNION
SELECT 'South East', 25, 950, 1.4, 1320 UNION
SELECT 'South West', 28, 674, 1.4, 940 UNION
SELECT 'Wales', 30, 460, 1.4, 647 UNION
SELECT 'Scotland', 23, 547, 1.5, 820 UNION
SELECT 'Northern Ireland', 40, 302, 1.4, 430 UNION
SELECT 'UK', 26, 6604, 1.4, 9000 )
INSERT INTO [fact].Petmetrics
SELECT a.AreaKey, (SELECT PetKey FROM dim.Pet Where PetDescription = 'Wolf') AS PetKey,
d.PopulationwithPetsPerct,d.HouseholdswithPets000s,d.Petsperhousehold,d.Petsperregion000s
FROM CTE_DOGS d
INNER JOIN dim.Area a ON d.AreaDescr = AreaDescription
WITH CTE_CATS (AreaDescr, PopulationwithPetsPerct,HouseholdswithPets000s,Petsperhousehold,Petsperregion000s)
AS
(SELECT 'North East', 14, 195, 1.5, 286 UNION
SELECT 'North West', 16, 520, 1.6, 795 UNION
SELECT 'Yorks and Humb', 19, 443, 1.6, 680 UNION
SELECT 'East Midlands', 20, 480, 1.8, 854 UNION
SELECT 'West Midlands', 17, 400, 1.7, 662 UNION
SELECT 'East', 20, 512, 1.8, 876 UNION
SELECT 'London', 14, 428, 1.5, 580 UNION
SELECT 'South East', 20, 890, 1.8, 1422 UNION
SELECT 'South West', 21, 514, 1.6, 810 UNION
SELECT 'Wales', 22, 360, 1.7, 596 UNION
SELECT 'Scotland', 15, 381, 1.6, 590 UNION
SELECT 'Northern Ireland', 14, 106, 1.5, 160 UNION
SELECT 'UK', 18, 4995, 1.6, 8000)
INSERT INTO [fact].Petmetrics
SELECT a.AreaKey, (SELECT PetKey FROM dim.Pet Where PetDescription = 'Lion') AS PetKey,
d.PopulationwithPetsPerct,d.HouseholdswithPets000s,d.Petsperhousehold,d.Petsperregion000s
FROM CTE_CATS d
INNER JOIN dim.Area a ON d.AreaDescr = AreaDescription

Setting up Power BI Dataflow in service

As per the recommended approach to Power BI at Enterprise level, a dataflow is going to be added to a dev workspace

Next, Create a data flow

And add all your connection details

Select the tables, in this case its my two dimensions and fact table. then click Transform data.

No transformations are required. All the Keys have been changed from int to text in this dataflow.

Save and Close and Refresh. this dataflow has simply been called Pets

Dev Shared Dataset

Now we are going to create the data set over the top of the dataflow. with the Enterprise Approach in mind we are going to create our shared dataset, containing the model and the DAX. other users could then decide to create reports over this shared dataset.

This is an incredibly simple dataset, and obviously, you will be dealing with much more complex data.

  • Open power BI desktop.
  • Get Data
  • Power BI dataflows

Choose the tables and in this case load the data because no transformations are required

Make sure the model is ok

create some basic DAX

Pets Per Household = SUM('fact Petmetrics'[Petsperhousehold])
Households with Pets (000s) = SUM('fact Petmetrics'[HouseholdswithPets000s])
Pets Per region (000s) = SUM('fact Petmetrics'[Petsperregion000s])
% Population with Pets = AVERAGE('fact Petmetrics'[PopulationwithPetsPerct])

And over this a very basic test report is created

Power Query in Power BI. Set dataflow Parameters

Before we move on. Later we will need to copy this and change the dataflows from Dev to prod. An easy way to do this is to set up parameters

In Power BI go to Transform data

And create another parameter for dataflowID

You can then right click on a Query and find these values specific to working with dataflows. Copy and paste the IDs to Workspace and Dataflow Current Value.

If you go into the dataflow in Service, you can also find these details in the URL.

Once your parameters have the correct information. Go into Each Query Advanced Editor and change the query to using the parameter rather than the hardcoded value

Source{[workspaceId=workspaceID]}
{[dataflowId=dataflowID]}

This means that you simply have to do this once, When you Copy to Production, change the IDs in the parameters to change the data source.

Once completed Close and Apply

Publish the Report

This report is now published to the Dev Workspace

The report has been saved as Dev_Pets and Saved to the Dev Pets App Workspace

Now we are in the position where we are in development in Power BI Service.

In this example, we have checked everything in development and we are ready to move on to create the reporting Pbix file.

It is recommended to create all your reports in a separate pbix file and just use the shared data set for testing visuals

Create the reporting Pbix

  • Open Power BI
  • Get Data
  • Power BI Datasets
  • Connect to Dev_pets
  • The model and all the DAX is pre prepared. recreate your reports. Imagine in a real life scenario, this would be a much more polished version of your test reports
  • There is now a Live connection between the power BI Dataset and the reporting Dataset.

Save and Publish the report

And again, save to the Dev workspace

There is a dataflow

A Dataset and a test report over the dataset (dev_Pets)

and a Report (Pet Statistics in the UK) live connected to dev_Pets dataset

We are ready to move to Production

Production Workspace

We now create a Production Workspace

Move Dataflows to Prod

Back in dev workspace, go to the dataflow and click on …

  • Choose Export Json

It downloads to the Downloads folder.

  • Open the JSON in Notepad ++
  • We are looking for each query to update:

Source = Sql.Database

and then the database \”Dev_PET_DB\”)

For this example, only the database needs to change.

You may also wish to change the name of the dataflow in the JSON file

  • This JSON File can then be saved.
  • Go back to the Production Workspace

+ New Dataflow

  • Open the JSON file that has just been amended

This will be imported into power BI

And you will probably need to establish your Production Credentials

And I can immediately see that we are in Production because our cats and dogs have got fiercer.

This will need to happen every time you move to Prod. Export the JSON and update the information about the data within the JSON file.

Power BI Desktop

We have the following pbix files

And a Production Folder has been created. Copy both of these reports and add them into Production

Dev has been renamed to Prod. these can be opened and Published to Prod

Open up Prod_Pets in Power BI desktop

Go to transform data

Now you can simple change the parameters to prod to change the data flow source. You have already set each query to use the parameter in Dev

  • Where does the production IDs come from?
  • go back to the power BI Service. Into the Production dataflow and get the URL

https://app.powerbi.com/groups/workspace ID Number/dataflows/Dataflow ID Number

Once the dataflow source has been changed, Close and Apply

This would be an easier process if you were connected to your SQL Database. You could simply change the data source. Dataflows make this task much harder to do.

  • Then Publish to Prod

Open up Prod_Pets from the production Folder in Power BI desktop

This has a live connection to the dataset that was just published. We need to change it from dev to Prod

  • And change to Prod_Pets

You can then tell your report has changed, in this case my animals have changed.

If your data is the same in production and development it becomes a lot harder to establish that you have done the right thing

Again, Publish your reports

Test your Production Reports

Now its time to test your Reports to make sure they are working ok.

What about Dashboards?

So far, we haven’t covered dashboards in this situation. This is dealt with automatically within the pipeline, but without the pipeline, how difficult is this to deal with?

Create a Dashboard in Dev

  • back in development workspace, lets pin a couple of visuals to a dashboard

we can do this by using get Quick Insights over the dev_Pets dataset. there is only one insight because the data set is so small but we can pin this to a dashboard

For the target dashboard. create an empty dashboard in Production

Now we have more content in dev, but it looks like without Pipelines, there is no way of moving the dashboard easily.

It looks like you have to use a Power BI REST API

https://docs.microsoft.com/en-us/rest/api/power-bi/dashboards/clonetileingroup?WT.mc_id=DP-MVP-5003835

How to access Power BI REST APIs programmatically

but the process is very involved and requires you to go tile by tile.

There is also a way of doing it in Powershell but again the process is complex and time consuming.

How to connect to (and query) Power BI and Azure using PowerShell

After reading some of these documents, if you are happy using Powershell or REST APIS these may be ways forward. Otherwise you will have to recreate your dashboards from scratch in Production. Its about weighing up which will be faster for you.

Creating Apps

We have a dev Workspace and a Prod workspace. In this situation I may offer an app in development to the testers. The app in Production is for all the Report users.

  • With this in mind go back to the Dev workspace
  • And do the same with the production App from the production workspace. the word Production is removed from the App.

And of course for each of these apps you can set up Navigation and Permissions.

Conclusion

There are multiple issues here outside of Power BI Premium.

Dataflows have already proved difficult to work with outside of the Premium environment and here they cause issues when attaching the production shared data set to the Production dataflows. Imagine having multiple reports and many queries to deal with. there are way to many error points in this process.

There is also an issue with the dashboards at present.

It would seem that this set up may be too much to deal with outside of the Premium environment using Pipelines.

Its possibly one to avoid if you

  • Have many reports
  • Have many dashboards containing alerts etc.
  • Have large data models with many queries in Power Query Editor
  • Use Dataflows
  • Aren’t fully familiar with using REST APIS or Powershell for Power BI if you have Dashboards

In this case, the only options are:

  • Move to Power BI Premium and start using Pipelines (Proviso on Pipelines working with Dataflows)
  • Simply have one workspace as dev and use your App as Production
  • Think about Power BI Premium Per User license and move to Pipelines
  • Understand that if you go this route, the time from dev to Prod may be considerable and there must be extra testing in case there has been anything missed along the way.

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