A Fine Slice Of SQL Server
Leila Etaati shows off some new functionality:
One of the interesting features of the New Card visual is the capability to add images to the Card visual.
It added more context to the car visual.
In this blog post, I will show some data related to cancer in New Zealand based on gender and cancer type.
Read on for the example.
Comments closedChris Webb diagnoses an error:
One of my most popular blog posts of the last few years is this one on the “Visual has exceeded available resources” error in the Power BI Service:
https://blog.crossjoin.co.uk/2020/01/20/visual-has-exceeded-the-available-resources-error-power-bi/
This error only used to appear in the Power BI Service, but the good news is – and trust me, this is good news – it may now appear in Power BI Desktop too following the May 2023 release.
It’s not often good news that you get a new error, but knowing that the Service will behave a certain way and replicating that on Desktop, at least it prevents an issue from popping up in production that you can’t find during initial development.
Comments closedMarco Russo and Alberto Ferrari break the ties:
DAX already offered two ranking functions so far: RANK.EQ and RANKX. While RANK.EQ is very seldom used, RANKX has been the primary ranking function for a long time. We wrote several articles about RANKX: one of them deals with ranking on multiple columns, a scenario that requires some DAX acrobatics to be solved as described in RANKX on multiple columns with DAX and Power BI.
The new RANK function makes ranking on multiple columns much easier because it offers sorting by multiple columns as a native feature, because it belongs to the family of window functions. Thanks to the concept of current row in window functions, RANK also helps in a subtle issue with RANKX – which despite being rare, might affect ranking on decimal numbers as described in Use of RANKX with decimal numbers in DAX.
Read on to see how you can use RANK() and how it compares to RANKX().
Leila Etaati breaks out Power Query:
There is a common way of seeing data in Excel as a Matrix format; many data entries look like a matrix in many contexts, from accounting to health data. However, to better analyze data and add more calculations and charts and, in general, get more insight from data, we need to change the matrix data in Excel to a tabular format in Power BI.
For example, below table, we have data about the Deaths from Cancer of Lip, oral cavity, and pharynx by age, sex, and year.
Not surprisingly, Power Query does a really good job at handling this common Excel style.
Comments closedPaul Turley lays out an explanation:
Back in December, I posted this short article about how Power BI can participate in Continuous Integration & Continuous Deployment (CI/CD), from simplified code sharing and version control all the way up to fully-automated Build automation & deployment scenarios. However, since the product inception, there have been significant challenges in orchestrating versioning and code sharing with a single PBIX file. Achieving DevOps and CI/CD was possible but it required creative work-arounds and manual steps. In April of this year, Nathan Hales contributed this post, showing how to use Tabular Editor to manually decompose a PBIX file into a Model.bim and then create a Git repo and Azure DevOps project.
Although the essential pattern is the same, the need for manual steps and work-arounds is eliminated with this new feature release!
This is really good news, and Paul shows you how to enable the feature (currently in preview) and use it.
Comments closedErik Svensen tries out an updated visual:
In the June 23 release of Power BI desktop we has been blessed with a new card visual that not only will give a better performance compared to adding multiple cards in the past but it also gives us some formatting options we have been dreaming of for a long time.
Here is a link to the official blogpost – New card visual | Public preview | Microsoft Power BI Blog | Microsoft Power BI
On social media you have probably already seen a lot of examples of usages, and I wanted to share how you can add a sparkline to the card to make it look something like this.
Erik does a good job of showing off the capabilities of this updated card visual.
Comments closedLast month there was a new update that has been made that provides support for drillthrough report actions in the Power BI service (Microsoft Fabric)! Those of you who are familiar with SQL Server Reporting Services (SSRS) know what a great feature this is to include in your reports to allow users to jump to another report for additional information such as detail level report and even allow the ability to pass the context (parameters) to the report.
Drillthrough was a big item that might have been a blocker for some companies preventing them from migrating from on-prem SSRS or Power BI Report Server (PBIRS) to the Power BI, well not anymore:)
So how does this work?
Read on to learn more, including something which is in Power BI paginated reporting but not SSRS.
Comments closedAllison Kennedy has a new title:
Today’s post is a short one with a video to demonstrate what I have learned. I’m a big believer in providing your end user with as much information as possible. Someone new should be able to pick up the report and understand it without needing to get a degree in Power BI or go digging through your company’s intranet to learn what’s what.
One of the neat features that Power BI provides, is the ability for any visual to act as a filter or ‘cross-filter’ to other visuals. This provides us with comparative values and highlighted bars, but Power BI tooltip just says ‘highlighted’, which isn’t very helpful.
Click through for a bit of DAX code which can help with that, as well as a video demonstrating how it all comes together.
Comments closedJason Cockington share some advice:
From my experience, most people who have reports built on a DirectQuery connection into their data source did so because of a lack of understanding of what the DirectQuery connection was designed to achieve. For the vast majority of reports, Import mode is the best solution for working with data in Power BI. DirectQuery should really only ever be applied when you are trying to solve one of the following challenges.
- Real-time Data – you need to see the latest available data from the source
- Huge Datasets – you have many billions of rows of data (more than 10Gb) so you just can’t import it into Power BI
- Regulatory Compliance – the data must stay in the source for data security/privacy reasons
Click through for more information.
Comments closedLeila Etaati smooths the curve:
The calculation will be done for all rows, till we don’t have the anymore data ahead ( 3 rows ahead) as you can see it will finished on row 2018 as 2018 is the average of 2018, 2019 and 2020.
so in the moving average we will miss some data point but replacing with average of data.
Less data point but help us to see a clear trend.
Click through to see how to do this. Moving averages is really good for the reports in which you want to get a rough magnitude but don’t care about exact values and don’t want oscillations to throw you off. For example, if I need to know how many seats to reserve for an event, I might use a moving average of the last several events as my baseline, rather than the prior event’s number.
Comments closed