Power BI. Created Reports in your ‘shared dataset file’ and now want to move them to a report pbix file. How do you go about this task?

The recommended approach to Power BI as an enterprise solution is to have your ‘shared data set in a pbix file where you can just create test visuals to check everything is ok.

Then create the real reports in a separate pbix file live connected to the dataset.

But what happens if you create great reports, including Bookmarks etc in the shared data set before deciding to move everything?

Changing the data source

Instead of creating a new pbix file and copying all the visuals in (this wont really work if you have bookmarks and more complex reporting set up)

First, save your ‘Shared pbix’ file with another name which will becomes the reporting pbix file. The original pbix file complete with the original reports can be left as is.

You could change the data sources over to the ones in the data set. However this creates an issue.

The Data set pbix file sits on dataflows.

If you currently try and change to data sets, Data sets aren’t offered.

So what do you do?

Remove Queries

In this example all the M Code for the Query should be done in the Dataflow within service. the only M Code in the shared data set should be the connection to the data flow.

All the Queries should be deleted. If you make sure your dataflow queries have the name you want in the dataflow, Re adding them back will be fairly straight forward

Close and Apply your Query

Back in Power BI all your visuals show as having issues. There is no data.

Go to Get Data and now you can choose datasets

Find the data set and select. This should then load in Live data from the data set and your visuals will be displayed again.

Publish this back up to service.

At this point you can look at Lineage to view that you are using the power BI recommended approach

The App

When I create the app for Viewing I simply hide the Dev reports from the users.

This appears to be the speediest way of moving your reports to their own file, if you have already done a lot of reporting work in the ‘shared data set’

Microsoft Business Applications Summit 2021. Power BI Vision and Roadmap

Driving a Data Culture

This is the 6th year of Power BI. Power BI has always been about driving data culture and has been rapidly evolving throughout its data journey.

Power BI is top of the Gartner Magic Quadrant and growing exponentially across users and business. Lets have a look at where we have come from and where we are going.

The Power BI Journey

Power BI started by wanting to empower Business Analysts. The next step was to empower IT departments

At the beginning of the journey the two targeted user groups wanted different things.

Business Analysis want quick BI with no red tape. IT wants governance, control and repeatability. By 2018 Microsoft was starting to think about both of these user groups and how Power Bi could work with each use case.

These use cases split into Enterprise and Self Service BI.

Microsoft moved to bring both Enterprise and Self Service together. Power BI was proving so popular it seems the best development was to bring enterprise reporting and semantic models into power BI

The following licensing was created to allow for this economic disruption

Built on Azure and deployed in over 50 data centers. Power BI used the cloud to bring about economic disruption

The cloud also offers a great economic model (Economies of Scale). Originally we had free and Pro for our business analysts. Premium became available in 2017 as an enterprise solution.

Enterprise And Self Service Converged

By 2018 with power BI, Microsoft aimed to

  • Empower every individual
  • Empower every team
  • Empower every organisation

Moving on to 2019 and 2020

Power BI increases its market share considerably and with every month of development comes huge changes to the product. Its now becoming a game changer for both self service and enterprise use.

AI Capabilities

Information workers need more, and power BI gave us more with inbuilt AI capabilities.

Key Driver Analysis

Key influences Visual

A great visual to look at the influences on your data. I have used this, for example to look at what drives negative tweets for a company. It also segments your data into understandable groupings

Smart Narratives

This visual provides textual analysis of your whole report or specific visuals. It will update the narrative dependant upon what the user selects.

This is a great visual for users who need to see descriptions along with the visuals to get a better understanding of the narrative.

Root cause Analysis

This is fantastic for users who want to create their own journey through the data. Select a metric and then allow the user to choose how they want to slice and dice the information. AI will find you categories with the lowest and highest values against the metric

Q&A

Q&A allows users to ask natural language questions, and Power BI will bring back the best visual that answers that question. developers can put together lists of possible questions for the user to choose from.

Powerpoint for Data

To make Power BI easy to use Microsoft decided to match experiences where ever possible to Powerpoint and Excel. This leads to massive adoption because people find it easy to use. they have already seen and used the ribbon in lots of other Microsoft products, take up is therefor a good option.

Moving to 2021

2021 brings to the table a new licence that gives smaller businesses the ability to buy in Premium licenses at a user level rather than pay for a Premium node.

This can work out much cheaper for smaller companies so you don’t have to miss out on Premium services.

AI Capabilities for Business Analysts

Again, our information workers require more from the service

Power BI has the most complete AI capabilities in any BI product. Along with the visuals mentioned above, the Business Application Summit introduced us to Sentiment Analysis and Key phrase extraction in more detail.

Sentiment Analysis

Azure has given us cognitive services for a while. For example, I used Azure to get tweets via Logic Apps and assign sentiment scores to each tweet.

With Premium, we can do this within Power BI. You will now be able to run data items in Power BI through sentiment analysis and assign scores. Are those reviews coming through from your customers positive, negative or neutral?

Key Phrase Extraction

Another fantastic cognitive service that I used to do pre moving the data into Power BI. Now you can get a list of key phrases from your data, and put them into a word cloud. All available within power BI

Automated Insights (Coming Soon)

Brand new Automated Insights are coming…

Automate insights will give you Anomalies, KPI Analysis and Trends out of the box.

Anomaly Detection will automatically find anomalies in time series data and also attempt to explain these anomalies. Along with this you can also see trends in your data and get explanations on these trends. Trends and anomality’s gives you a holistic overview of your data

And KPIS look at our Goals which is new in Premium. We will look at this new feature later.

Automated insights proactively prompt us for time critical information, but you can get insights without being prompted by clicking the Automated insights button.

It works without any set up or configuration (Apart from KPIs because this needs Goals to work with.

AI for Data Scientists

Extend with Azure ML

Create ML Models

Python and R Integration

Explore Predictions

Going beyond on the power BI Journey (What is coming)

Insight to Action through Power Platform

Power Apps has been available for some time to embed into a Power BI Report but there has been a lot of work done in this area to make it work better within the power BI suite.

I have used a Power Apps Visual to allow users to send data back to a database, which would then display within Power BI as it was a direct connection.

New features include Power Automate within Power BI. You can now add a button in Power BI that will trigger Power Automate. I cant wait to look at some use cases for this new service.

One question I have is regarding Logic Apps within Azure. Logic Apps is the same service as Power Automate and I want to know why the decision has been made to call the same product two different things. And if Logic Apps can stand in for Power Automate in this situation.

Performance management

Power BI Goals is in Public Preview and available for Premium users

Goals is a new Power BI artefact that you can set up on your metrics that matter the most to you. You can assign data from reports to update your goals and users can drill through into your reports for further analysis.

Another fantastic new service, its a shame its only offered to Premium users. Thankfully Premium per user allows buy in to these new services for smaller companies.

My one concern is if you are using Premium Pipelines to host Development, Test and Production workspaces.

We are still waiting for dataflows to be added to this feature, its doubtful whether goals will be included when introduced.

This would mean that you cant move your goals from dev through to production so hopefully I am wrong about this.

Real Time Analytics

Power BI Streaming Dataflows

Streaming dataflows should be coming later in 2021 as preview.

Streaming dataflows is a brand new concept in power BI, and for the first time will offer the ability to combine multiple data sources into a streaming dataflow.

This is again another Premium feature

Front line workers

Insights on the Move

There have been significant improvements to the mobile apps which are getting great reviews from both Apple and Google stores.

Empowering Every Team with Teams

Great Teams use data and we can embed Power reports in teams channels so we can add Power BI reports to meetings and provide links within chat.

Microsoft have put a lot of work into bringing the Power BI Service into Teams for much better collaboration. They want Power BI to be as fundamental to what you do as your calendar, meetings or chat.

It’s recommended to make sure that you make sure the Power BI App is always available in your tools panel

One issue I have with Power BI in teams is having to navigate away when you are using chat. If I am looking at a document in Teams and I see that someone is chatting to me, it can be annoying to have to leave the document to see what else is happening. Hopefully they sort this functionality out.

Power BI In the real world with HoloLens

HoloLens 2 vs HoloLens 1: what's new? | 4Experience's AR/VR Blog

Straight out of science fiction. The HoloLens 2 allows you to augment Power BI Analytics over your real life journeys. This gives you Analytics where ever you go.

I would need to think about how and when you would need this but they gave a great example of walking through an office and having virtual tv points up on the walls.

New Announcements for Power BI analytics

In part two there was lots of exciting announcements of new features coming to Power BI

Drill down and drill through on the tooltip

Power BI has given us a few ways to do drill down and drill through.

For drill through, You could right click on a visual or even create a button to click to drill through on the highlighted item.

Drill down was available as an icon at the top of a visual

But very soon it should be even easier to establish that these options are available. Power BI Will soon have both Drill through and Drill down available on the tooltip.

Paginated report within your Power BI reports. Vertical Headers. etc

Build a Paginated report table in report builder with vertical headers, grouping, nesting etc and then add this visual to your Power BI report

New Standard Table visual in Power BI

These new options will be added to the table visual. This is the current experience

But soon we will be able to add sparklines within the table, both column and line sparklines.

This is one of the biggest requested additions so its great to see that we will soon have sparklines on the standard table visual.

Buttons Bookmarks and Navigations

I have been using Power BI for a few years now and the one thing I have always disliked is the workaround feel of creating button navigation. Having to layer buttons or visuals over the top of other eachother and hiding and unhiding where appropriate. It was time consuming and overly complex.

Microsoft are working on new navigator features to set up new custom navigation. This is one of my favourite new features.

Have a few bookmarks on a page and want to switch to different bookmarks. Then use Bookmark navigation. Just drag it in and you will get configurable navigation on all your bookmarks.

How about Page Navigation. Same again. Simply drag page navigation onto your pages.

This is fantastic and you can even use custom navigation so users can only navigate to specific pages . It would be great if you could add images to these buttons too but lets see how things develop.

Other Announcements

  • Paginated reports inside Power BI.
  • Smart Narratives going into General Availability
  • Anomaly Detection going into General Availability
  • Automated Insights is shipping later this year
  • Data set hub to recommend promoted and certified datasets
  • Excel – Connect to data sets using Get Data in Excel
  • Coming soon, the ability to create Power BI Apps and turn it into a Teams App, bringing Teams and Power BI together
  • Quick Create from Sharepoint lists
  • Live connected to the datasets in order to connect to multiple datasets being updated.

Governance and Scalability

Microsoft Information Protection

MIP is becoming an even more important part of security in Power BI and across all Microsoft services. This is a complex area and requires much more research. Including what Information protection service is best for you. We will look at this in more detail in another post.

Its important to note that there are additional costs per month to this service.

Scalability

No matter what the data volume is, your queries should always run fast

Automatic Aggregations

Based on the existing aggregations feature. If a user happens to drill down to detailed reports the system will automatically reverts to direct query, rather than the imported data.

Previously, this had to be set up by the developer but moving forwards the aggregations will be created for you.

Coming later this year and brings together Power BI and Azure Synapse Analytics (If using the Azure Warehouse as the underlying database)

Large Models Feature

Another Premium feature. Used with incremental refresh a dataset can grow up to 80% of the premium capacities total memory.

Hybrid Tables

Used for fast real time analysis.

Partitions are created by year and your current year will be set against real time data. This is such an exciting announcement. I cant wait to get started with it. (Premium only)

Streaming Dataflows

Azure Stream Analytics is used for this. (See Power BI Streaming Dataflows)

(Premium only)

Conclusion

The Microsoft Business Applications summit was again, full of really exciting new innovations.

However, Its becoming really clear that those on pro licenses are now really missing out on features like Goals, streaming dataflows, machine learning, etc.

At the beginning of this journey, the big factor for moving to Premium was simply to give viewing access to many more people, along with the security that power BI provides. This is simply not the case any more.

Thankfully Premium per user licenses gives smaller companies a way to move to Premium at lower cost. the barrier to entry has been significantly lowered and it seems that Microsoft expect us to move to those licenses if we don’t want to get left behind.

it should also be noted that those that have Power BI Premium through their E5 licences can simply pay the difference and move up to the Premium per user licenses.

Another slight negative was the fact that there are issues with features already available that were not dealt with at the conference. The big one for us at the moment is the fact that Premium Pipelines simply don’t work with dataflows.

When the recommendation has been to use dataflows to separate this job out from the pbix file, it seems a real shame that they have not acted accordingly to get this into Pipelines (Maintain Development, Test and Production areas)

Another feature of Power BI that is lacking is source control. there are hopefully some new features coming to configure with DevOps. It is to be assumed that any changes to this will be Premium only.

With this in mind, its still exciting to see all the new updates, and the fact that they are tying Power BI in much more strongly with the other Power Platform offerings.

What was your favourite announcement from the Microsoft Business Applications Summit this year. I would love to hear your thoughts.

Autoscaling with Power BI Premium Gen 2

We have been working with Power BI Premium for a few weeks. Simply switching it on and seeing how it goes.

However, Its worth paying some attention to Autoscaling that you can get with Premium Gen 2 (Preview)

Auto Scaling

Previously our Power BI Premium capacity could struggle when there was high capacity. For example If we reached full capacity, someone’s automatic refreshes would fail. Or if too many things were happening on the server, report users would find that reports were taking longer to render.

There are lots of use cases where this could happen so Auto scaling is definitely something that can help with these issues.

You can now scale and autoscale using Azure Pay as you go, which is around £62 per vCore for a 24 hour period

We use the DTU Pricing structure in Azure for SQL DBs. What is the difference between the DTU and the vCore pricing structure?

Autoscaling is an opt in feature and can be charged to an Azure Subscription

Once the spike is over, scale down happens and you stop paying for the scale up.

Autoscale Notifications

Toasts pop up in Admin Portals Capacity Settings to let your admin know when autoscale is running.

It would be good to be able to tell everyone working with Power BI when this is happening simply for reference

Get Started with setting up Autoscaling in Azure

Go into Azure and Select Subscriptions. You need to have made the decision before hand on which subscription can be used for Autoscaling billing.

Next create an auto scaling resource group

Enable Autoscale in Power BI Admin Portal

To do this you need to be the Power BI Admin (Or Global Admin)

Another addition is that the person needs to be at least a contributor on the Azure Subscription to go through all the steps succesfully

Go to Capacity Settings

Make sure Premium Generation 2 is already enabled

Then Select Manage Auto Scale

Enable auto scale and then select your Azure Subscription

And then assign the number of vCores to the Autoscale

Here we have set the max of 2.

How many vCores does a Premium P1 capacity have?

8 virtual Cores

Once completed you are all set. There are some questions. Apart from the Toast pop ups are there other ways to monitor and log the usage of Autoscaling?

This needs its own page but there are Apps you can try like https://appsource.microsoft.com/en-us/product/power-bi/pbi_pcmm.capacity-metrics-dxt?tab=Overview

The big takeaway from all this is that we should never be in a situation where we are surprised that we have reached capacity. Or, if we do set up Auto Scaling it should not be used on a day to day basis.

More investigation is needed on how to set up proper monitoring so we have full knowledge about what is going on in Premium Capacity. And we must never forget that there will be Pro workspaces already set up and these shouldn’t go under the radar either.

We will have a look at these issues in future posts

Power BI March 2021 Updates – Direct Query for Power BI datasets and Analysis Services, Testing the new fixes.

Direct Query for Power BI datasets and Analysis Services feature has currently been in preview for a couple of months

Switching this feature to on, should hopefully allow us to create reports over multiple data sets, which will allow use to have smaller datasets, maybe just over a single model. These can then be connected together in the report

And we couldn’t wait to try it out.

We had two data sets. And for one report we wanted to connect to both datasets so we could create reports over the two, without having to create an entirely new larger data set.

However we ran into issues which ended up rendering this unfit for purpose

  1. None of the formatting was remembered from the original datasets
  2. All the folders had disappeared that had been set up in model view
  3. All the Sort by items had gone.
  4. Both models connected to a data dimension, but actually removing one of the date dimensions (from the second model) and connecting the second model to the first models data dimension didn’t seem to work very well.

We have lots of use cases where this would be perfect. so in the March update, it is mentioned that the team have been working on this. Lets have a look at see if this is now a viable option for us.

The source data sets

Data set 1

We have some folders for the measures

In the date dimension, month has the sort order of Month No

Seasons has the sort order of Seasons order

And we have a measure set as a Percentage (An example of formatting)

Data set 2

We have again, Folders, Sort orders and Formatting.

Both datasets have a date dimension

lets look and see what happens if we use Direct Query for Power BI datasets and Analysis Services

Remember to turn it on as a preview feature in options and settings

Get data

Choose a dataset (That has been published to an app workspace

Go to model view and remember to upgrade the model view

Issue with layout views

At this point, one of the key issues is that in the shared dataset pbix file, the developer has created multiple layouts in model view to make it easier to work with.

In the report pbix file all the layouts are lost and we are left with the All tables layout.

Not good because the report developer has to redo this work again in this report file

So here is the first model

Import data set 2

we can now get data from another Power BI dataset even though we are connected up to a dataset. Previously you could only connect to one data set.

What does this mean?

With one data set its a live connection, in the same way as you would live connect to analysis services. with Live connection there is no local model.

Direct Query. Direct Query needs a local model adding into the report so in this case, a dataset also gets published to Power BI Service, along with the report.

From this in Power BI Service

To this

Select Add a Local Model

And select the next data set

In this case we are happy with the security because both data sources are within the same workspace and we trust the owners and admins in this workspace.

Click OK

As the report developer I am now looking at quite a complex model in all tables.

The colours denote the two data sets.

Now we need to establish which tables are in twice.

Immediately we can see date and date 2 and these need conforming

You cant delete a table. All you can do is hide it in report view.

In this case date 2 is being hidden (Hide in report View)

And a join is being created between the metrics table in data set 2 and the date table in dataset 1

Remember that you will need to go over your model. Find every table that is being used across the models. Hide duplicates and create relationships

Check for issues

The date table in data set 1 has the above Sorts applied and they are still working in the report

The measures folders are still available in both dataset 1 and 2

However Formatting has been lost on the Percentage measure.

So this leaves us with one major issue across datasets, and we can’t reset all the formatting within the reporting pbix file

As it stands then this is currently not fit for purpose and just needs another extra tweak. Its a real shame because we were really hoping to use this very soon. Hopefully Power BI Sorts it out in the next release.

Power BI external Tools – ALM Toolkit

How do you do schema changes to your model without refreshing the entire model?

This is especially applicable for large models using incremental refresh where refreshing the entire data set takes a long time to process.

The ALM toolkit really helps with this process

The examples I am going to use aren’t incremental refresh but it will hopefully give some idea on how to use the ALM toolkit

And a big proviso here. You can only do this with Premium workspaces

Source

Open your model in Power BI desktop. From here go to External tools and open the ALM Toolkit (Ensure you have the latest version of the AML toolkit downloaded)

The source has already been populated against the open model. We now need to set the target

Target

Go to the service. Workspace Settings.

At this point the workspace needs to be in Premium

You need to copy the workspace Connection which is only available in Premium. Once copied, add into Workspace

We can see that the pbix file and the data set in service are identical. ‘Same Definition

Lets make some changes

Adding a new measure

add a new measure in your desktp pbix dataset.

Total Product Standard Cost = SUM(FactResellerSales[ProductStandardCost])

And back to ALM toolkit.

Before continuing, go into Options

Make sure that the Processing Option is default and that we are only going to process affected tables

For table updates, retain partitions should be checked, This is very specific to Power BI Incremental loading. Incremental loading works with partitions and we don’t want ALM toolkit to go to the database and affect any of the partitions ‘For example you could have a partition for every year’

Click  Compare

And then Select Actions

Hide Skip objects will get rid of everything that hasn’t changed.

Now we can see the one new measure

We want to add the new measure without completely refreshing the data set

Then go to Update

Are you sure? message is returned

Quick note on XMLA Endpoints

At this point you need to have Read Write enabled on the XMLA endpoint

“XMLA endpoints enable open-platform connectivity to Power BI datasets. With these capabilities, customers can leverage a single one-version-of-the-truth semantic model across a range of data-visualization tools”

https://powerbi.microsoft.com/en-us/blog/power-bi-open-platform-connectivity-with-xmla-endpoints-public-preview/

To do this you need to be the Power BI Admin or global Admin. In Admin Portal > Capacity settings > Workloads > XMLA Endpoint = read Write

If the next step doesn’t work you may need to speak to your Admin about the above. this is because we are using an external tool to update the schema.

When I tried this, I didn’t notice errors but the changes started to add up as I went along the process.

Back to the Update

Click OK to are you sure? and the measure is quickly updated. the database wasn’t read or updated. All that happened was a quick schema update.

Why would you want to run an upload, full or Incremental for new measures? this is the perfect way of introducing those new measures as quickly as possible.

Adding a calculated Column

Adding calculated columns aren’t advised because they don’t get compressed in the tabular database, Its always worth doing this in Power Query Editor or ideally in your source reporting database.

Back in the desktop file

A simple calculated column is created.

In ALM toolkit go back to Options

Again, the following options should be set

Then go to Compare. Select Actions and Hide Skipped Objects

And here is the new calculated Column.

Next click Validate Selection

If we were working with Incremental refresh and partitions you would see all your partitions here along with the above information.

If you have these partitions when you update you will see a process message, but don’t worry, it hasn’t done any data processing at the source, its simply added the new column and processed only within the model.

You can go into Power BI Service and do a quick Edit on a report,

drag the new column in to see that there is data for that column, but nothing else has been processed.

Adding new tables or new columns at source or in Power Query Editor

In this case we actually need the data to process.

  • The measure just needed the DAX to be added to the model.
  • The calculated column simply used the data already within the data model without doing a process.

For this new logic we do need to process the data.

Back in the ALM toolkit you need to untick, for table updates retain partitions because we now need to pull the data in for all the partitions and process all that data.

Process only affected tables is an important option here, We don’t want to process anything but the new table or column.

Once you have the settings set above you can go on to validate and update. And importantly this time the new data will be processed into the model, rather than just a schema change.

And every partition will be processed on an incremental load because of the change to the settings.

This is an excellent way of dealing with updates on large models but its important to note

  • Only available for Premium
  • Ensure Admin Settings – Read Write enabled on the XMLA endpoint

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

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.

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.

Power BI Admin. Increasing awareness when publishing a report – December 2020 Updates

It is very easy for Power BI Developers to create and then publish reports to the service without much thought.

It will be different from company to company, but it would be great to remind developers each time they publish that there are certain standards that need to be maintained for each published report

With the December 2020 Update there is now a way for the Power BI Admin to create a message for your report Developers on Publish.

The power BI Admin (or global Administrator) can go into Power BI Admin Portal

As the Admin, lets add a message for our users to make sure they understand the importance of the security on the App workspace.

Should they be using Security groups rather than email addresses?

There are many considerations that you can address here (to 5,000 characters)

This new setting may take about 15 minutes to work and become part of the publish process.

Once set up, every time you publish you will see the disclaimer

This gives your developers a final reminder of all the checks they need to do before publishing.

This is a great new addition to the Admin tenant settings.

Power BI when to (Possibly) use a Bi Directional Filter in your data model

Power BI Loves a Star Schema and It loves single direction joins, one to many from your dimension (Description) tables to your central fact (Business metrics) table

The reason for the single direction filter join? You want to be able to filter your measure by descriptors. Sales by Product category. Quantity Sold by Business Unit.

There isnt a need to filter a descriptor by a measure. it cant happen.

This is nice simple logic which works really well. However, there are some use cases where this may not apply. Lets look at our Activities model to get more of an idea of this in action.

Activities Model

  • The Date table is used in lots of other models and has dates from 1990 to 2035 in it.
  • This model only has 10 years of data and its important that the latest date for all the DAX and Filters is not the current date but the last date in the data
  • This model is at year level and the last year in the data set is Currently 2019 (We are now in 2021)

the first thing to do is to test that the flags are working

  • Year from the date table
  • Flags from the flag table

And this works fine. There are only flags to 2003 to 2019 so all the years not attached to these are omitted and its all fine.

Then Activities measure from the fact table is added and it all seems to go wrong (Keys have been added to show the issue)

Note that Activities are 0

The Key (dateKey from dim to fact, FlagKey dim to fact) are essentially cross joining. There should only be one year.

If you Filter the Table so Activities are greater than 0 everything is resolved. The Fact is being filtered.

What is happening?

When the measure comes back as 0 or Null, we are not filtering the fact table

So we want to filter year by the flag but there is only a single direction filter to the factor table. Without the filter on the fact table, its almost like there is now a block in the middle, not allowing other filters to work.

You only see this because:

a. You want to see metrics that are null or 0

b. If the flag was in the date table rather than a separate dimension then there wouldn’t be an issue. Because its in another dimension it cant filter the year.

For this specific issue, the joins between date and the fact and the flag dimension and the fact has been changed from Single Direction to cross join.

Now the flag table can filter the year if we aren’t filtering the measure.

Why are cross joins not recommended in power BI?

There is always a performance issue when you do the bi directional join so you should only do this if you have to.

Bi Directional Filters are one of the top Power BI performance Killers because Power BI has to work much harder with that join

Other Ways to Resolve the issue

Resolve in SQL

The Flags are specific to the report date NOT the current date. But, if the Date dimension was created in SQL Pre Power BI, these flags could have been added in the Date table. Then simply imported into Power BI within the Date dimension

Resolve in Power Query Editor in Power BI

  • With the Date Dimension and the flag dimension still intact in Power BI.
  • In Power Query Editor, Merge Flags into date,
  • Add in the Flag for the last 10 years into the date table.
  • Then Filter the date table so there is only 10 years worth of dates.
  • This would ensure you didn’t need to cross filter join so long as the criteria is that you want to see 10 years of data

Power BI Premium Per User now in preview (December 2020 updates)

One of the main benefits of Power BI Premium is the ability to share with hundreds of users who don’t all have to have their own Power BI Pro license at £7.50 a month.

At a certain level, Premium becomes less costly than giving everyone who needs them Pro licenses. its said, you need 500 or more users for Premium to make sense.

However, its not just about having the ability to have hundreds of people viewing your reports. There are many more reasons to have Premium. There are lots of enterprise style features not part of Pro. Enterprise of course comes with the ability to have larger and speedier models.

This is a real issue for smaller businesses who cant take advantage of Premium per capacity, P1 P2 or P3 nodes.

However, there now may be an option to have premium capabilities without having a Premium License.

Premium per user is targeted at small and medium businesses because, if you are not a large enterprise, the Premium price point of just under £4K every month can be eye watering.

Premium extends Power BIs licensing model

Lets have a look at some features between Pro, Premium Per User and Premium

Model Size

  • Power BI Pro 1 gig per data set. Workspace Max 10 BG
  • Premium Per user 10gig (Per model)
  • Premium Per Capacity 10 gig (Per model. can be refreshed up to 12)

Refresh Rate

  • Power BI Pro 8 refreshes a day
  • Premium Per user 48 refreshes a day
  • Premium Per Capacity 48 refreshes a day (Gen 2 has significantly improved refreshes)

Paginated reporting

Paginated Reporting comes with Report Builder. the free tool for creating Paginated Reports. You can build paginated reports over a model created with power BI, or other data sources and publish to a Power BI workspace in the same way as a Power BI Report

Use a paginated report if you want to do printing or PDF generation. they are great for Sales invoices for example. Power BI reports are used for exploring the data.

  • Power BI Pro Can use Report Builder Free but cant publish to a Pro workspace
  • Premium Per user Yes
  • Premium Per Capacity Yes

AI Capabilities

Apply ML Model in dataflows

Impact Analysis in Service

AI Insights in Power Query Editor and Dataflows

  • Power BI Pro No
  • Premium Per user Yes
  • Premium Per Capacity Yes

Advanced Dataflows

For example, direct query and the ability to create compute and liked entities (actions that perform in storage computations)

  • Power BI Pro No
  • Premium Per user Yes
  • Premium Per Capacity Yes

Usage based Aggregate Optimisation

Aggregations allow you to manage large tables. You can have tables at a higher level of granularity, aggregated within Power BI, for example at year level, which are imported into Power BI. When you want to drill down to lower level detail, you can then move to the detailed data in Direct Query mode. aggregations should generally only be used for really large models.

  • Power BI Pro Yes?
  • Premium Per user Yes
  • Premium Per Capacity Yes

Deployment Pipelines for Application Lifecycle Management

  • Power BI Pro No
  • Premium Per user Yes
  • Premium Per Capacity Yes

XMLA Endpoint Connectivity

XML For analysis protocol. XMLA is used to connect to the Analysis Services engine which allows Power BI to have all the features of Analysis Services.

A major draw for this feature is the ability to create your shared one view of the truth data model within Power BI. And allow that model to be used by other analytics services, not just Power BI

  • Power BI Pro No
  • Premium Per user Yes
  • Premium Per Capacity Yes

Enhanced Automatic Page Refresh

Available as settings within the Power BI Admin Portal.

  • Power BI Pro No
  • Premium Per user Yes
  • Premium Per Capacity Yes

Multi Geo Support

Helps multinational customers deploy to data centres around the world, rather than just the home data centre.

  • Power BI Pro No
  • Premium Per user No
  • Premium Per Capacity Yes

Unlimited Distribution

This is the big one for Power BI Premium. the ability so share content with many users without individual Pro licenses. We will look more into this later

  • Power BI Pro No
  • Premium Per user No
  • Premium Per Capacity Yes

Power BI Reports On Premises

Using the Power BI reports Server. This option gears up an enterprise for moving fully to the Power BI Premium service later.

Updates to the specific Power BI Desktop (for on premesis usage) are much slower that Power BI Desktop for Service. You get reduced functionality. For example, no dashboards.

  • Power BI Pro No
  • Premium Per user No
  • Premium Per Capacity Yes

Bring your Own Key

Power BI encrypts data at rest and in process and uses Microsoft managed keys to do so. Premium allows you to use your own keys which sometimes makes it easier to meet compliance requirements. It gives you extra control.

  • Power BI Pro No
  • Premium Per user No
  • Premium Per Capacity Yes

Getting Premium Per user?

Upgrade to Power BI Pro and then upgrade to a Premium per user license

This will extend until general availability

Do we know what the Price point is yet? No. At the moment its free but without the knowledge of the actual pricing this is a hard one to take up before general release

Premium per user overwrites the Power BI Pro user license so there is no need for both

The Power BI Premium per user Workspace

You need to create your workspace. then go to settings and assign Premium per user capacity afterwards.

Only other developers with a premium per user license will be able to access the workspace.

This is a major point. If you are a team of 4 working in one workspace. Each user needs the Premium per user licence. So none of your developers with Pro licenses can work within this workspace.

None of your report users can access the report via the app without having Power BI Premium Per Users either.

Without that price its incredibly difficult right now to look into how this will affect the business as a whole. essentially it would mean switching everyone up to Power BI Premium Per user Licenses

Do we know if Premium Per user will be bundled into the Office 365 E5 Offering?

Currently if you have E5 licenses Power BI comes with the package. With Premium per user, will this become part of the E5 package?

It looks like E5 customers can purchase Premium per user as an add on to Pro but again, there is no specific information on this as yet so its difficult to tell how this will effect things.

So, as usual there are lots and pros and cons to this new license and we need a lot more information on pricing to be able to make any decisions.

But the ability to use features that are tempting you across to Premium, that’s really interesting. I thought that maybe there would be a case for going through your reporting portfolio to see if you have a mixture of cases for Pro and Premium per license but what with Dataflows, Pipelines etc, it would be difficult to establish a split between the workloads.

This is one to watch

Power BI Premium Gen 2 First Look

Currently Premium Gen 2 is in Preview (Jan 20201) but it looks really exciting for those with Premium capacity. Lets have a look at Gen 2 and see how it differs to Gen 1

Gen 1

With Premium Gen 1 we are bound by the number of vCores and by the memory we have. Lets take the P1 SKU as an example

P1, P2 P3 P4 = Are all Premium SKUs. Each one has more vCores for better performance

SKU = Stock Keeping Unit

vCores = Virtual Cores is a puchasing model which gives you more control over compute and memory requirements.

When it comes to Premium, reports would slow down if there were two many queries running. And if people were using many models at the same time you would have to wait for your time slot.

As you can see, there is only 25 gig memory across the data sets Once a report isn’t being run and used any more, that memory gets dropped and is added back into the pool.

Report users and report developers are also fighting with report refreshes.

Premium Gen 2

Gen 2 is not in generally availability yet but if you have Premium you can switch to Gen 2 in preview.

In Power BI Admin (as the Power BI administrator or Global Admin)

Go to the Capacity Settings and switch Gen 2 from disabled to enabled.

You can also go back to Gen 1 if you need to but if you do make sure you flag up any issues you are having.

lets have a look at the model compared to Gen 1

Autoscaling

The end users encounter the throttling and performance issues with Gen1 because they physically only have 4 backend vCores. Now with Gen2, Autoscaling allows you to deal with spikes. This is not available yet but will be coming. This is helped by the fact that there are other vCores that can be called on.

If you do come up to the 4 core Limitation it will, or may lend you a vCore so you don’t see impact for your end users

Previously our admins had to deal with this kind of problem but this will really help automate these kind of issues

Memory

Data Sets can go over the 25 gig memory capacity. Previously Premium was 25 gig for all the data sets. Now Data sets are gated individually.

This is a fantastic update. We don’t have to worry about the collective size of all our data sets.

Refreshes

Previously there was a maximum of 6 refreshes at any one time. Otherwise you can get throttled.

With Gen 2, refreshes get spread out over a 24 hour period and don’t impact other queries from users. refreshes just run

The looks great. People are seeing refreshes of an hour and a half coming down to 10 minutes.

Capacity Usage Metrics

This is coming soon and will have a breakdown of items.

Its a little annoying when you have set up gen 2 and want to view the metrics to see how everything is working but currently can’t.

With Gen 2 we will also be able to work against a chargeback model. This means that we can spread the costs of Premium between distinct areas of an organisation dependant upon their usage.

Workloads

Again the workload settings aren’t fully functional at the moment but more will be coming.

For example for data set workloads we can specify minimun refresh intervals and execution intervals. we can detect changes in our metrics.

We don’t have settings for dataflows and AI yet.

Why go with Premium Gen 2 Checklist

  • Performance benefits
  • End users see faster reports
  • Refreshes, we now don’t have refresh bottlenecks and we remove refresh failures due to throttling
  • Premium per user
  • Improved metrics will be introduced soon
  • Autoscaling
  • Proactive admin notifications

Why it may be worth waiting until Preview becomes GA

It looks like people are having some issues with dataflows and there is already be a known issue about this

It looks like this might be fixed quickly, and once dataflows are OK, it seems like. A workaround is to move your dataflows out into another Workspace and then back in but hopefully this will get much better.

Questions

Is Premium Gen 2 going to be the same price as Gen 1?

Is there any way to find out how many dataflows you have if dataflows are an issue?

Will we still give great functionality to the Power BI Pro users?

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