A Fine Slice Of SQL Server
Prathy Kamasani gives us options:
A colleague of mine came to me with an interesting use case, “ Switch between a summarized value or selected value with multiple legends”. For example, I have five countries and their GDP values. When the end user goes to the report, the user would like to see the average GDP of all countries, but when the user selects single or multiple countries on the slicers, the line chart should show only selected values.
Click through for the guide.
Comments closedPaul Turley sends us an e-mail:
Using common language is critical but often trivialized, when describing requirements, deliverables and project expectations. When people are working together, depending on each other to complete important tasks, they must have a clear understanding of the common language and terminology. It is usually only after a word, phrase or abbreviation has been used with an assumed meaning that we realize the error and have gotten ourselves into trouble. Often, on a daily basis, I review project proposals and requirement documents containing inaccurate language related to Power BI project work. I also getting a lot of virtual eye-rolling when correcting seemingly inconsequential language. But I can also cite many cases when subtle misinterpretations became costly mistakes.
This is at a higher level than naming measures or dimensions.
Comments closedGilbert Quevauvilliers reads the chain of custody documents:
As often happens blog posts originate from a customer requesting something I have not figured out before.
In this example the requirement was to be able to determine which data sources were being used by which tables, which were then associated to one or many Power BI datsets.
While I was working through this I figured out I could take it one step further and also if required have the actual Power Query as part of the report.
Read on to see what Gilbert came up with.
Comments closedTeo Lachev goes error-hunting:
A scheduled SSIS job that executes a massive DAX query to an on-prem Tabular server (Power BI can also generate this error) one day decided to throw an error “Source: “Microsoft OLE DB Provider for Analysis Services.” Hresult: 0x80004005 Description: “MdxScript(Model) (2020, 98) Calculation error in measure ‘Account Snapshot'[Average utilisation % of all CR active current accounts last 3 months]: The result of a conversion or arithmetic operation is either too large or too small.” At least we know the offending measure, but which row is causing the error? The query requests some 300+ measures for 120 million customers, so I thought someone might find the troubleshooting technique useful. Let’s ignore what the measure does for now except mentioning that it performs a division of two other measures.
Click through for the technique.
Comments closedRobert Blackburn builds a dashboard:
We must periodically evaluate the state of our databases. Luckily for SQL Server, Microsoft provides us with a customizable assessment through their SQL Assessment API Repo and API Documentation. You can change the rules per database and output the results to a database to track history.
However, that will take more than an hour. Let’s create a dashboard with the default rules in under an hour. We will use Azure Data Studio (ADS) and Power BI Desktop (PBI). If you are not familiar with them, both are free. Azure Data Studio is automatically installed with SSMS 18.7 and higher. You can also install them individually.
Read on to see how this works. Granted, it will not auto-update but unless the assessment output format changes between runs, at least you wouldn’t need to modify Power BI and could just refresh the data.
Comments closedMarc Lelijveld investigates a what-if scenario:
One of the topics discussed during the session, is the effect of deployments on datasets by using native deployment pipelines in the Power BI service. Deployment Pipelines only deploy meta data from the data model, however specific changes might have an unwanted effect on the data in the dataset in the target stage.
In this blog post, I will further elaborate on several specific use cases and the effect on your dataset in the target stage.
Read on for the results of three separate tests.
Comments closedIf you’re monitoring activity in Power BI, for example using Log Analytics, you’ll know that you can capture the DAX queries generated by your published Power BI reports. How do you make sense of them though? You may want to know which tables, columns or measures are being used by a query – maybe so you can work out which ones aren’t being used and can be deleted. I always thought the only way to do this would be to parse the DAX query, which would be incredibly difficult to do. Yesterday, though, Igor Cotruta pointed out on Twitter that there’s a really easy way to do this that I didn’t know about, using the DISCOVER_CALC_DEPENDENCY DMV. I’ve used this DMV before and blogged about it here, but what was new to me is that you can pass a DAX query into the QUERY restriction (it is all documented here). To see how it works let’s look at a simple example.
This looks pretty cool.
Comments closedImke Feldmann wants to know when the work is done:
If you have been working with Power BI for a while now you might have come across the standard Power BI actions in Power Automate. They allow you to automate a nice bunch of Power BI processes. But while there is a trigger that starts a flow when a Power BI dataflow action has completed, no such trigger is available for when a Power BI dataset action has (successfully) completed. So here I will present a workaround that is still possible without a premium Power Automate license.
Read on for that workaround.
Comments closedMarco Russo and Alberto Ferrari aren’t satisfied with a single date:
The best practice when we have multiple dates is to create a single, shared Date table and to connect it to all the date columns with different relationships. When a table has more than one date column, only one relationship can be active while the other relationships are inactive. In our sample model, the Date table connects both Sales[Order Date] and Sales[Delivery Date] with two relationships: one is active (with Order Date) and one is inactive (with Delivery Date).
Read on for a couple of options and what they mean for your visuals.
Comments closedMatt Allington made the Power BI world a slightly better place:
Have you ever loaded a calendar table with lots of numeric columns (such as Year, Month Number, etc), loaded it into Power BI, and then had to manually go an turn off the default aggregation on these columns? If you build Power BI reports, then I bet you have done this more than once. Jeffrey’s idea was that Power BI should be smart enough to detect a dimension table (one side of the relationship) and to disable these default aggregations. There’s nothing worse than adding a Year column to a table and having Power BI add the years together. If I add a year to a table, I want to slice and dice, not SUM the years.
Matt added a request and see where that gets you.
Comments closed