Power BI Governance, Good Practices, Part 2: Version Control with OneDrive, Teams and SharePoint Online

Power BI Governance, Version Control with OneDrive for Business, Microsoft Teams and SharePoint Online

One of the most important aspects of the software development life cycle is to have control over different versions of a solution, especially in a project where there is more than one developer involved in the implementation. Just like when you normally create a project in visual studio and you commit the changes back to a source control system like GitHub or Azure DevOps, it’s advised to keep the history of different versions of your Power BI reports. What we expect from a source control solution is to keep tracking of all changes happening in the source code while developing a project. So you can easily roll back to a previous state if you like to. 

The other benefit of having a source control process in place is when multiple developers are working on a single project. Every single one of them makes changes in the source code then they commit all the changes into the source control server without overwriting each others’ work. 

With Power BI things are a bit different though. Power BI report files are PBIX files which are stored in binary format (well, PBIX is basically a zip file isn’t it?) which at the time of writing this post, there is no official way to enforce Power BI source control in any source control solutions like GitHub or Azure DevOps (YET). 

Microsoft announced a fantastic feature last week (6/05/2020) named “Deployment Pipelines” which does exactly what we’re after, but it is currently a preview feature which is only available only to organisations with Power BI Premium. So it is out of the game for the majority of us.

Having said that, there is still a way to keep history of changes in the shape of different versions of PBIX files. This is called Version Control.

There are several ways you can enable version control over your PBIX files while developing the report. Regardless of the version control platform you need to think about having multiple environments and who can access them for doing what.

EnvironmentAccessible toDescription
DevelopmentDevelopersData modellers and report writers access this environment for development purposes.  
User Acceptance Test (UAT)Developers, SMEs, Technical Leads, Power BI AdminsAfter the development is finished the developers deploy the solution to the UAT environment. The solution will then be tested by SMEs (Subject Matter Experts) to make sure the business requirements are met.
Pre-prod (Optional but recommended)Technical Leads, Power BI AdminsAfter the solution passed all UAT testing scenarios Technical Leads or Power BI Admins will deploy it to Pre-prod for final checks to make sure all data sources are correctly pointing to production data sources and all reports and dashboards are working as expected.  
ProductionTechnical Leads, Power BI Admins, End UsersAfter pre-prod checks completed Technical Leads or Power BI Admins deploy the solution to the Production environment which is then available to the end users.

Version Control Options

If your organisation does not have a Premium capacity then “Deployment Pipelines” feature is not available to you. So you need to come up with a solution though. In this section I name some Version Control options available to you

  • OneDrive for Business
  • Microsoft Teams/SharePoint Online
Continue reading “Power BI Governance, Good Practices, Part 2: Version Control with OneDrive, Teams and SharePoint Online”

Highlighting Below Avg Sales per Hierarchy Level with SWITCH() and ISINSCOPE() DAX Functions in Power BI

Highlighting Below Avg Sales per Hierarchy Level with SWITCH() and ISINSCOPE() DAX Functions in Power BI

I was working on a project a wee bit ago that the customer had conditional formatting requirement on a Column Chart.
They wanted to format the columns in the chart conditionally based on the average value based on the level of hierarchy you are at.
Here is the scenario, I have a Calendar hierarchy as below:

  • Calendar Hierarchy:
    • Year
    • Semester
    • Quarter
    • Month
    • Day

I use “Adventure Works DW2017, Internet Sales” Excel as my source in Power BI Desktop. If I want to visualise “Total Sales” over the above “Calendar Hierarchy” I get something like this:

Line Chart in Power BI, Total Sales by Year

Now I activate “Average Line” from “Analytics” tab of the Line chart.

Adding Average Line to Line Chart in Power BI

When I drill down in the line chart the Average line shows the average of that particular hierarchy level that I am in. This is quite cool that I get the average base on the level that I’m in code free.

Power BI, Drilling Donw in Line Chart

Easy, right?

Now, the requirement is to show the above behaviour in a “Column Chart” (yes! visualising time series with column chart, that’s what the customer wants) and highlight the columns with values below average amount in Orange and leave the rest in default theme colour.

So, I need to create Measures to conditionally format the column chart. I also need to add a bit of intelligent in the measures to:

  • Detect which hierarchy level I am in
  • Calculate the average of sales for that particular hierarchy level
  • Change the colour of the columns that are below the average amount

Let’s get it done!

Detecting Hierarchy Level with ISINSCOPE() DAX Function

Microsoft introduced ISINSCOPE() DAX function in the November 2018 release of Power BI Desktop. Soon after the announcement “Kasper de Jonge” wrote a concise blogpost about it.

So I try to keep it as simple as possible. Here is how is works, the ISINSCOPE() function returns “True” when a specified column is in a level of a hierarchy. As stated earlier, we have a “Calendar Hierarchy” including the following 5 levels:

  • Year
  • Semester
  • Quarter
  • Month
  • Day

So, to determine if we are in each of the above hierarchy levels we just need to create DAX measures like below:

ISINSCOPE Year		=	ISINSCOPE('Date'[Year])
ISINSCOPE Semester	=	ISINSCOPE('Date'[Semester])
ISINSCOPE Quarter	=	ISINSCOPE('Date'[Quarter])
ISINSCOPE Month		=	ISINSCOPE('Date'[Month])
ISINSCOPE Day		=	ISINSCOPE('Date'[Day])

Now let’s do an easy experiment.

  • Put a Matrix on the canvas
  • Put the “Calendar Hierarchy” to “Rows”
  • Put the above measures in “Values”
Detecting Year, Semester, Quarter, Month and Day hierarchy levels with ISINSCOPE in Power BI Desktop

As you see the “ISINSCOPE Year” shows “True” for the “Year” level. Let’s expand to the to the next level and see how the other measures work:

Continue reading “Highlighting Below Avg Sales per Hierarchy Level with SWITCH() and ISINSCOPE() DAX Functions in Power BI”

Quick Tips: Line Chart and Area Chart Conditional Formatting in Power BI

Line Chart and Area Chart Conditional Formatting in Power BI

In this post I show you a very quick trick to format Line Chart and Area Chart conditionally in Power BI. As this is a “Quick Tip” I’m going to keep this post really short.

One of my customers asked me to show time series in line charts and area charts. But she want’s it to be conditionally formatted based on the average value over time. Let’s keep it simple, she wants to show “Sales by Year Month” in line chart, but, highlight the data points that are below “Average Sales per Year Month”. As you may know, we currently do not have the luxury of formatting line charts and area charts. But wait, this post is all about that. Let’s dig into it.

From the above scenario, you perhaps already guessed that we need to create a measure which defines the colour based on “Average Sales per Year Month” to be able to format the chart conditionally. If any data point is below the “Average Sales per Year Month” then we highlight it in Orange, if it is above the “Average Sales per Year Month” then we stick to the default colour.

Let’s do it.

Continue reading “Quick Tips: Line Chart and Area Chart Conditional Formatting in Power BI”

Power BI Ecosystem Report Authoring Tools Demystified

Power BI Reporting Tools Confusion

There are a lot of discussions these days around Power BI tools to create reports and for sure many of you may have already downloaded and worked with some of them if not all of them. You may also already thought that some of the tools’ names are confusingly similar. I recently had an interesting conversation with fellow who has a lot of SSRS report writing background. I was talking about Paginated reports and said, I downloaded the latest version of Power BI Report Builder… that he immediately said, wait a second…

  • John: Power BI Report Builder? Oh I see, that’s the one that you can create paginated reports with then you can deploy those reports into an SSRS instance.
  • me: NOPE! That’s not the case I’m afraid.
  • John: Oh I know, I meant Power BI Report Server, you can deploy the reports to an instance of Power BI Report Server. I knew it!
  • me: NO! That’s not what I’m talking about…
  • John: What the…?

I bet some of you had similar conversation with a friend or a customer. OK, in this post I explain a little bit about report authoring tools available to you and your organisation to get the most out of your Power BI ecosystem.

Here is a list of all reporting tools currently available to you:

  • Power BI Service: It is a SaaS (Software as a Service) offering from Microsoft in the cloud. The users in an organisation, based on their access rights, may be able to create and publish data, reports, dashboards in Power BI Service. The users can also schedule data refreshes on the published data as well as securely sharing and distributing the contents. While creating or editing reports is possible in Power BI Service, it is strongly recommended to avoid this method for several reasons. The most obvious one is that the changes you make in a report may be soon get overwritten by someone else that republishes the same report from Power BI Desktop. Check this blog post from SQLChick to see why you should avoid creating or editing reports directly from Power BI Service. The reports are downloadable in PBIX format. Use Power BI Service here.
  • Power BI Desktop: It is a desktop report authoring tool that can be used to connect to, or loading data from, varies types of data sources, preparing, transforming and cleansing that data and at last visualising the data. Power BI Desktop is the predominant report authoring tool with a lot more functionalities and flexibility than Power BI Service. For instance, setting up Role Level Security (RLS) is NOT available in Power BI Service. The format of the report file is PBIX. Download Power BI Desktop from here.
  • Power BI Report Builder (Paginated): Paginated reports aka “pixel perfect reports”, as the name resembles, are formatted in a way to fit perfectly on a page. That report page might later be printed. You have exact control over the page formatting to display your data in tables or charts. The reports are not as interactive as Power BI Desktop reports are. Paginated reports are based on RDL technology which is standard report format in SQL Server Reporting Services. The tool for developing paginated report in Power BI ecosystem is Power BI Report Builder. The reports file type is RDL. You can currently publish Paginated reports only to a Workspace that is backed with a premium capacity. Download Power BI Report Builder from here.
Continue reading “Power BI Ecosystem Report Authoring Tools Demystified”