Power BI Can you use an inactive join for a slicer (USERELATIONSHIP)

Imagine the scenario. You are dealing with two dates. date A and B. You create an active and an inactive relationship to your date table.

You can create Dax with USERELATIONSHIP for any measures that use the inactive join. Great for the bar charts, line charts etc.

But what if you have a slicer for Year on the report? At the moment that slicer is connected to Date A because you simple drag year from the date table.

This report needs to be sliced against Date B. Is there a way to do this?

Lets look at one of our measures that uses USERELATIONSHIP

YTD Measure =

CALCULATE(TOTALYTD([Number of Records],’Date'[Date]), USERELATIONSHIP(Metrics[DateKeyB],’Date'[DateKey]))

The USERELATIONSHIP can only be used with CALCULATE,CALCULATETABLE, CLOSINGBALANCEMONTH, CLOSINGBALANCEQUARTER, CLOSINGBALANCEYEAR, OPENINGBALANCEMONTH, OPENINGBALANCEQUARTER, OPENINGBALANCEYEAR, TOTALMTD, TOTALQTD and TOTALYTD 

From this it is clear you can only use it in a measure with a metric.

And you cannot use a Measure in a slicer. Slicers have to be created from a column.

Which means that our inactive dates can’t be used in a slicer. And this is problematic because if you have a page of time based visuals all using the USERELATIONSHIP then its a fair shout that you are going to have a slicer too for example ‘Year’

So can we come up with a workaround?

Workaround 1. Adding date information to the fact table

Out model rules are

  • DateKeys in the Fact table. I also hold the dates hidden just in case
  • The dateKey Joins to the date Dimension which contains Year, Day, Month etc

So what I am going to do in this case is add my relationship B details into the fact table just for the time being.

s.[DateB] AS [Date B],
--Workaround 1
DATEPART(Year,s.[DateB]) AS [Year B],
DATENAME(Month,s.[DateB]) AS [Month B],
DATEPart(Month,s.[DateB]) AS [Month No B],
[staging].[fnQuarter](s.[DateB]) AS [Quarter B],

I have created a Quarter function with the specific quarter logic which is use for every Quarter period.

This is then refreshed into the Power BI Dataflow

And then refreshed into my data set.

All ready to work with. What I decided to do in Power BI was create a table containing those values.

Support End Date (For Slicers) = 
SUMMARIZE ( 'GrowthHubMetrics', 
GrowthHubMetrics[SupportDateKey],
'GrowthHubMetrics'[Support End Quarter], 
'GrowthHubMetrics'[Support End Month], 
'GrowthHubMetrics'[Support End Month No], 
'GrowthHubMetrics'[Support End Year], 
'GrowthHubMetrics'[Support End Date])

The dates in the fact table were then hidden leaving the above Slicer table.

And then I remembered that Date time Measures don’t work without a continuous date table and DateB isn’t continuous.

But then I remembered that I had already put in a lot of work creating all the date time measures on the inactive join to the date table using USERELATIONSHIP so actually all the date time measure are fine.

Would I go back and create a date table for dateA and a date table for DateB so I can have slicers and drill down to the date. Its very possible but that renders the use of USERELATIONSHIP Pretty null and void, unless you still want to slice these visuals against DateA.

Connect the DAX table to the model.

the date Table for Slicers is connected up to Dimdate in the model and we are ready to go

So all the measures are still connected to the date table through the inactive join

But the slicer can be set up over the new DAX table

I’m hoping to get a better way of doing this as we go because it seems that you should be able to do this without having to create another table.

Update

In the end, this became so complex and issue heavy (Drill throughs not working properly etc) I gave up. Created a reference of the date table for Date B. Connected this up. removed the DAX table and changed all my measures to get rid of USERRELATIONSHIP.

So Pages 1 to2 use DateA and Pages 3 and 4 use DATEB.

As a conclusion, if you are wanting to use Drill through and Drill down I think I would recommend role playing dimensions. the complexity of the USERELATIONSHIP with just seems incredibly complex at the moment.

Its a shame because I love the idea of switching to a none active join but in practice its proved unworkable.

If you have any tips on this please let me know

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

Quick Guide of Power BI Premium Features

It can be quite infuriating to be a Power BI Pro user and constantly be on the verge of doing something, before realising that its only available with Premium.

Thank goodness for Power BI Premium Per User for smaller companies. At just double the price per user licence, all these enterprise level goodies can be available. I wanted to do a whistle stop tour of each one, and some others I have found along the way

Automated Machine Learning

No code machine learning is great if you arent a data scientist and you want to try out some basic machine learning.

For this example I have gone to my dataflow in Power BI Service

I am going to use my date dataflow just as an example, but obviously this isn’t the datasource you would want to use

I wont go any further with this example as its not a great one but I just wanted you to get a feel of the first few screens. This is an incredibly powerful feature. once set up you can use this dataflow in Power BI.

You can also integrate Azure ML models that your data scientists have created in Azure with the Azure ML API

Cognitive Services

I have previously used Cognitive Services in Azure to add sentiment analysis and key phrases onto tweets as they come in via an Azure Logic App trigger.

This information is then loaded into Power BI Pre prepared.

I have struggled to access this functionality within Power BI previously but hopefully this will allow Power BI users proper access to this fantastic Azure Service

Within Power BI Query Editor (Dataflows in Service)

If you are in Pro you will see the following

With Premium however you can use the following functions

Just a couple of examples, you can take descriptive data and score it with ScoreSentiment. Then you can take these scores and add a new column for Sentiment (Positive, Negative, Neutral)

You can add a language field that will tell you if your test item is for example, English, German, French etc.

And you can extract key phrases from descriptive text to add a cool word cloud to your power BI report.

No code data prep and scale

Visual Data Prep is another area that needs looking at in more detail but this is available in Premium dataflows

You now get a great diagram view of all the actions done on your queries.

This will make things much easier for users who can now interact with the diagram view.

Deployment pipelines

Assign your development App Workspace and Pipelines will then let you create Test and Production App Workspaces. Each workspace can be pointed to different data sources.

You can then very easily work in development. move your work to test and then to production when its ready to use.

As at April 2021 Dataflows haven’t yet been added but once this is in, I think this is really the only way to go with Power BI.

Having done some research on Dev Test and Prod in Power BI Pro this makes a huge difference as its practically unworkable in Pro

Integration with Azure Synapse

Azure Synapse is the new Azure Data Warehouse.

You can now create Power BI reports over big data in Azure Synapse.

And Azure Synapse gives you even bigger wins with performance

Pixel-perfect paginated reports

Report Builder is free. You can download it and even use a model previously created in Power BI.

https://www.microsoft.com/en-us/download/details.aspx?id=58158

Here you can build your Pixel Perfect reporting, invoices are a good example. Reports that require page numbers and headers and footers that are most likely to be printed out.

Without Premium you cant publish the rdl files to the Power BI Service.

With Premium, you can publish your pixel perfect report to service along with your other Power BI objects

XMLS read/write

These Endpoints allow other providers access to your Analysis Services Engine within the Power BI Service. This means that you will be able to use even more tools for governance, monitoring, debugging, modelling etc, rather than only being able to use Power BI Desktop.

Your admin does need to allow this within the Admin Portal

Trillions of rows

With Premium, you can query and analyse 1 trillion rows of data. which is part of the ‘query performance over big data’ feature. In fact any large data set can make use of this feature to make refreshes and response times quicker

https://powerbi.microsoft.com/en-us/blog/aggregations-for-petabyte-scale-bi-available-in-the-power-bi-service/

This is worthy of a more deep dive feature in future but its certainly exciting.

Advanced Security

Here are some of the advanced security features that can be used for your most sensitive data

  • Compute isolation
  • Double Encryption at Rest
  • Double Encryption in transit
  • Private links
  • Zero egress
  • Immutable logs
  • TLS 1.2
  • Customer Managed Keys
  • VNet Network isolation
  • Immutable storage logs
  • FedRAMP high & DISA IL4
  • DISA IL5, DISA IL6 + IDC503
  • Vulnerability management
  • Automatic Certs rotation

End to End protection

Sensitivity labels and Microsoft Information Protection (MIP)

Sensitivity labels allows you to classify your data across all Microsoft products like power BI, Excel etc.

Its an extra cost and can be purchased standalone or through a Licensing suite like the Microsoft 365 Compliance Plan, Microsoft 365 Business etc.

For pricing you need to contact Microsoft at this time.

Other findings

If you are using dataflows in Pro, you cant create computed entities such as referencing tables. Merging tables.

This means that dataflows in Pro need to be quite simple. you only get the full functionality in Premium.

This is why most people in Pro prefer to do the data prep in Power BI desktop.

Its becoming more and more difficult for business users to remain with Power BI Pro, all these above features are an absolute must for enterprise level reporting.

It is really worth that switch to either Power BI Premium per user or a Premium node if you are a large enough company

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 Key Influences Error – A field in explain by is not on the ” table or a table from the same data source and related to it by a many to one relationship. Try Summarising it

The analysis is performed at the record level of the ‘table’ A field in explain by is not on the ” table or a table from the same data source and related to it by a many to one relationship. Try Summarising it

This model is all about behaviour and attitudes for an event company who put on IT events for companies who want to learn more about cloud based solutions.

The stakeholders are all the people who go on the courses, and those people who arrange the courses.

Its important for the company to know how their customers are reacting to their cloud based events and training. Which ones are doing well or not in terms of reactions.

The trainer or presenter sends out a questionnaire after ever event / course. they also send in their own questionnaire about how they felt the course was engaged with.

I have a Star Schema and in one of the dimensions I have a behaviours table. We want to know what influences behaviour from all the other attributes from around the star schema

There can only be a certain number of behaviour types so this dimension is set as a junk dimension. Each Type of behaviour is joined to the other using a cartesian Join

Every behaviour type is matched to every other behaviour type and then we can simply assign the correct row to the person event and theme

  • So a stakeholder can go to many events
  • A stakeholder can hold different behaviours for every event

We want to see what effects behaviour, so the Key Influences visual is the one we really want to use in this project

In this visual we are analysing by Explain by.

Add in a measure from the fact table and it works fine

But this isn’t telling us anything. We need descriptive information from the other dimensions

So lets go for something from Events

And here is where we get the error

The analysis is performed at the record level of the ‘table’

Obviously this part of the error makes sense because we want to understand the behaviour

A field in explain by is not on the ” table

That is correct. we are explaining by a field in another dimension

or a table from the same data source and related to it by a many to one relationship.

Try Summarising it

How to deal with this issue

the error doesn’t give much away but the solution lies in the model.

The recommended single direction join has been used on every single relationship. Therefore, the dimension can filter the fact but the fact cant filter the dimension.

And specific to this model, Another dimension cant filter another dimension

Events and behaviour cant filter eachother.

Unfortunately setting all the relationships to both didn’t resolve the issue either. Maybe the answer lies with DAX

Lets look at that error again

the Keyword in the error is SUMMARISE.

Now we know exactly what we want to use as the ‘Explain by’ Lets see if we can set up a Summary table using DAX

Key influencers Summarize table = 
SUMMARIZE (
    'Fact',
    'B & A table'[Behaviour],
    'B & A table'[Attitude],
    'Dim Events'[Event Title],
    'Dim Events'[Led by],
    'Stakeholder'[Name],
    'theme'[Theme]
)

To get around the fact the the dimensions are not joined to each other you simply start the summarise with the central fact table.

now we simply rejig to use the new summary table for this specific visual and we have a working solution

So when it comes to key influencers and star schemas, a great resolution is to create a summary table specifically for that visual

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.