Press "Enter" to skip to content

Category: Power BI

Role-Playing Dimensions in Power BI

Published 2020-06-29 by Kevin Feasel

Martin Schoombee explains the concept of role-playing dimensions and then explains how that works in the Power Bi world:

In technical terms a role-playing dimension is when a dimension table has multiple (foreign key) relationships to the same fact table. In more non-technical terms, it is when you have the same attribute (“Date” for instance) that can relate to the same metrics in different ways.

If you look at the data model below as an example, you can see the Date entity could be used to reference either the Invoice Date or Delivery Date from the Sales entity, changing the perspective of the metrics we’re looking at.

It’s a little surprising to me that there isn’t an easier way to handle this concept. Role-playing dimensions are a core part of the Kimball model, and they’re common enough that you’d expect support to be a bit simpler.

Comments closed

Pattern-Matching and Text Extraction in Power Query

Published 2020-06-29 by Kevin Feasel

Imke Feldmann shows how we can match specific patterns in Power Query, which lacks regular expresssions:

I plan to approach this by

1. stepping through the string and check each character if it is valid.
2. If so, store it
3. and if not, forget it. And in that case, also forget the stored values so far so the collection starts from scratch.
4. Then if a series of matches builds up, I will have to check the count of the stored values to not exceed the length of my target pattern.
5. Once the length is reached, no further checks shall be performed and the found values be returned.

My aim is to find a generic way so that this solution can be adapted to many other similar use cases as well. Therefore the pattern must be described in a scalable way and the identification of the pattern elements should be easy to compute.

It’s good to be able to adapt, improvise, and overcome, though this is exactly what regular expressions are intended to do. It’s odd that there appears to be no built-in capability, where instead you’d have to do something like bring in external languages like JavaScript.

Comments closed

More Fun with 1-Column Fusion in DAX

Published 2020-06-26 by Kevin Feasel

Phil Seamark continues a discussion on single-column fusion:

You may notice the [Package – Bag] measure uses the * (multiplication) operator in line 4 between a measure and what looks like a column filter.

The [base measure] performs a simple COUNTROWS aggregation and returns an INTEGER. This side of the equation makes sense, so let’s see what is going on with the DAX on the right-hand side of the * operator? The filter statement is encompassed with parenthesis, which automatically converts the expression to a TRUE/FALSE boolean value – which is then implicitly converted to an INTEGER value of either 0 or 1. It can’t be anything else.

The result of this double conversion is that we end up with a INTEGER * INTEGER to produce the number we see in the visual.

Click through for plenty more where that came from.

Comments closed

Creating a Time Dimension with Time Bands in Power BI

Published 2020-06-26 by Kevin Feasel

Soheil Bakhshi shares how you can create a time dimension with a granularity of seconds in Power BI and SSAS Tabular:

I wrote some other posts on this topic in the past, you can find them here and here. In the first post I explain how to create “Time” dimension with time bands at minutes granularity. Then one of my customers required the “Time” dimension at seconds granularity which encouraged me to write the second blogpost. In the second blogpost though I didn’t do time bands, so here I am, writing the third post which is a variation of the second post supporting time bands of 5 min, 15 min, 30 min, 45 min and 60 min while the grain of the “Time” dimension is down to second. in this quick post I jump directly to the point and show you how to generate the “Time” dimension in three different ways, using T-SQL in SQL Server, using Power Query (M) and DAX. Here it is then:

Click through for the code, which includes several sample bands (e.g., 5 minutes, 15 minutes) that you can also control.

Comments closed

Power BI On-Premises Data Gateway Error SpooledOperationMissing

Published 2020-06-23 by Kevin Feasel

Gilbert Quevauvilliers encounters an error:

I got the following error DM_GWPipeline_Gateway_SpooledOperationMissing”,”parameters”:{},”details”:[],”exceptionCulprit”:1

This error was caused because the current Virtual machine where the On-Premise Data Gateway was running was cloned and then started up.

Read on to learn about the implications and how Gilbert was able to solve this issue.

Comments closed

Differences between Tableau and Power BI Data Models

Published 2020-06-18 by Kevin Feasel

David Eldersveld lays out a few differences between Tableau and Power BI’s data models:

Prior to 2020.2, Tableau had a physical data model that allowed joins between tables. This layer is still present, and it is similar to Power BI’s merge capability within Power Query to join multiple tables into a single table.

With the introduction of the logical model in Tableau 2020.2, a single logical table may consist of one or more physical tables. Two or more logical tables may be related to each other. This approach shares many similarities with Microsoft’s tabular model, but there are currently some core differences that may impact how you approach data modeling in one tool versus another. It’s not always going to be a straightforward scenario to apply knowledge of how to build a data model in one product to building it in the other.

NOTE: This post considers some core differences between Tableau and Power BI modeling as of June 2020. It does not go into detail on announced roadmap features such as Power BI’s enhanced composite models coming later in 2020, which will allow scenarios like combining a “live connection” composite model with additional data sources, or even multiple live connection models.

Read on for four differences David has found.

Comments closed

Dynamic Measures in DAX

Published 2020-06-17 by Kevin Feasel

Kristyna Hughes explains the concept of dynamic measures in DAX:

For example, you may have three major stakeholders looking at a report: CEO, CFO, and COO. The CEO may be more interested in future profits and looks at trends in the number of loads booked to see where we are headed. The CFO wants to see profit trends on loads that have already been completed (actualized profit). Additionally, the COO would rather see what’s currently in transit and look at only picked up loads. You could make three pages, one based on booked loads for the CEO, another based on delivered loads for the CFO, and one based on picked up loads for the COO. But what happens if your report is already going to be multiple pages and needs room to grow? You would need to triple your page count to accommodate the needs of your users or build three completely separate reports! Don’t worry, dynamic measures can solve this problem for you without clogging up your reports or workspaces with extra measures, visuals, and reports.

Click through for the demonstration on how to combine this with a slicer to change reported measures.

Comments closed

Choosing an Algorithm for Table.Join in Power Query

Published 2020-06-15 by Kevin Feasel

Chris Webb continues a series on optimizing merge performance in Power Query:

The first thing to say is that if you don’t specify a join algorithm in the sixth parameter of Table.Join (it’s an optional parameter), Power Query will try to decide which algorithm to use based on some undocumented heuristics. The same thing also happens if you use JoinAlgorithm.Dynamic in the sixth parameter of Table.Join, or if you use the Table.NestedJoin function instead, which doesn’t allow you to explicitly specify an algorithm.

There are going to be some cases where you can get better performance by explicitly specifying a join algorithm instead of relying on JoinAlgorithm.Dynamic but you’ll have to do some thorough testing to prove it. From what I’ve seen there are lots of cases where explicitly setting the algorithm will result in worse performance, although there are enough cases where doing so results in better performance to make all that testing worthwhile.

That behavior is the same as if you decided to start writing INNER LOOP JOIN or INNER HASH JOIN for your queries. In the right spot, you may have knowledge the optimizer doesn’t have and can make performance faster, but a lot of the time the approach will be a bit too heavy-handed and end up a net degradation of performance.

Comments closed

Analysis versus Reporting and Power BI

Published 2020-06-12 by Kevin Feasel

Rob Collie thinks about industry movement between analysis and reporting. Part one gives us some backstory:

Excel was about to make a large investment in BI-related capabilities, and the powers that be had selected me to lead our part in it. I was excited, but now I needed a crash course in “what the hell is BI?” I was given multiple tutors, and they all were quick to introduce the concept of Analysis versus Reporting. The “versus” seemed to be pretty important. It wasn’t an “and” – no, the “versus” was chosen deliberately in these sermons. You see, these were Two Very Different Things.

I struggled mightily to grasp this difference. I was told that interactive things like PivotTables were Analysis tools – NOT Reporting tools! Reports were something completely different. “But,” I pointed out, “they’re called ‘Insert PivotTable Report’ on the Excel menu today!” (This was Excel 2003). “Yeah,” said the mentors, “…we might want to fix that.”

Part two explains why analysis and reporting are both important:

Another “meta characteristic” of paginated reports is that they TEND to display details rather than aggregations. EX: specific transactions rather than emergent trends. In paginated reports, you’re MORE likely (but not guaranteed!) to be looking at “raw” rows of data from the original database, whereas in a Power BI report, you’re more likely (but again, not guaranteed!) to NOT be seeing raw individual rows, but rather intelligent aggregations of MANY rows. But either way, more detail means you’re more likely to need multiple pages.

Rob’s right on the money. And I’m looking forward to part three of the series.

Comments closed

Incremental Refresh of Any Power BI Data Source

Published 2020-06-12 by Kevin Feasel

Gilbert Quevauvilliers wants incrementally to refresh all the sources:

The pattern that I am talking about is the following below, which will be used as my example below.

– Connect to a data source which can query fold.
> In my example I have installed and configured an Azure SQL Serverless DB
> In this database I have a date table.
– Configure date table to use Incremental refreshing as per the blog post
> Incremental refresh in Power BI
– Create a function which will then use the Date value as part of the parameter
> In my example I have got CSV files which have Exchange rate information from Azure Blob Storage.
> The file names of the CSV files is the date.
– Invoke the Function within the date table to extract the required information.

I know what you might be thinking, that as soon as I add in the column with the function it breaks the Query Folding. That is what I thought too.

The great news is that Incremental refreshing DOES STILL WORK!

Read on for the demonstration.

Comments closed