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Category: Power BI

Changing Power BI Models with Visual Studio Code

Published 2020-07-10 by Kevin Feasel

Phil Seamark has a integration I hadn’t expected to see:

Visual Studio Code is a reasonably new development environment which is a lightweight and quick install and get up and running. There is nothing you can do in VS Code that you can’t also do in another tool using TOM. I just thought it would be fun to show how quick and easy it is to get up and running in very few steps.

The following exercise uses VS Code to connect and manage a Power BI Desktop model. You can also connect to models hosted in Azure Analysis Services as well as models hosted in Power BI Premium.

Read on to see how to get everything going.

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The Importance of Power BI Deployment Pipelines

Published 2020-07-10 by Kevin Feasel

Marc Lelijveld explains the importance of Power BI Deployment Pipelines:

You might have seen the announcement, Power BI Deployment Pipelines have been released in May 2020. It is around for about two months now. On different social channels I have seen a lot of buzz around it already, both positive and negative honestly. Though, I think this is a great step forward!

Back in 2018, I posted a blog about multi-tier architecture and continuous delivery with Power BI. If you are not familiar with a DTAP approach and why this helps you to structure your development processes, I advise you to first read that blog. Personally, I am really excited about Deployment Pipelines! With this functionality, Microsoft starts offering an out-of-the-box functionality that helps you to easier move your Power BI content through you DTAP pipeline.

I think it’s a pretty big step in the right direction, though the “Why this isn’t so great” section is a bit lengthy.

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Moving a Semantic Model from SSAS to Power BI

Published 2020-07-09 by Kevin Feasel

Teo Lachev explains why it might make sense to move a semantic model from SSAS over to Power BI:

We decided to move the semantic model to Power BI so that Power BI owns the data. Besides potentially improving the report load time, this architecture has also other important advantages (to learn more, read my “Power BI Large Datasets: The Good, the Bad, and the Ugly” post). If you’re not on Power BI Premium, that “movement” might not easy if you have opted to use Visual Studio or Tabular Editor for development. That’s because Power BI Pro doesn’t expose the XMLA endpoint, so your only option is to migrate the model to Power BI Desktop. But migrating an SSAS Tabular project to Power BI Desktop is not officially supported and there is no automatic migration path.

Click through for the full explanation of why, as well as notes on the process.

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Performing a Power BI Risk Assessment

Published 2020-07-09 by Kevin Feasel

David Eldersveld has a set of questions to ask when building Power BI dashboards:

As with any important endeavor, businesses should be in a position to document and have a plan to mitigate any possible risks associated with deploying software. It is no different with Microsoft Power BI.

Note that the purpose of this post is simply an encouragement to evaluate risk exposure and consider how you would overcome potential future issues that could arise from any cause–it is not a caution against using external tools created by the wider Power BI community.

Read the whole thing.

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Understanding LOOKUPVALUE in DAX

Published 2020-07-08 by Kevin Feasel

Alberto Ferrari explains the LOOKUPVALUE function:

LOOKUPVALUE is one of the most widely used functions, especially for DAX developers who come from an Excel background. Indeed, the behavior of LOOKUPVALUE is very close to the behavior of the widely-adopted VLOOKUP function in Excel. Yet, there are important differences between the two; quite often, newbies use LOOKUPVALUE instead of creating a relationship between tables that ensures higher flexibility and higher performance.

This article is an introduction to LOOKUPVALUE. If you are interested in studying the internals of LOOKUPVALUE in more detail, make sure to check the advanced LOOKUPVALUE article; in that article, we describe the behavior of the function in detail along with several performance considerations.

Click through for the article.

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Configuring Power BI Incremental Refresh

Published 2020-07-01 by Kevin Feasel

Gilbert Quevauvilliers has a follow-up from a post:

Following on from my successful blog post How you can incrementally refresh any Power BI data source (This example is a CSV File), I found a way where I can just use dates created in Power Query to get data refreshing incrementally.

Full credit goes to Rafael Mendonç who actually figured this out. All that I have done is to translate what Rafael Mendonça did in his PBIX and put it into steps that you can follow along with.

https://www.rafaelmendonca.com/2020/06/incremental-powerbi-csv-api-excel-odbc.html

In this blog post I am going to demonstrate how to get this working with what I hope is very easy to follow.

Read on for the process.

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Tips for Improving Power BI Dashboards

Published 2020-07-01 by Kevin Feasel

Tino Zishiri has a set of tips to design better-looking dashboards:

There are several reasons why you should design great looking dashboards. Here are a few;

– They make information more accessible – end users benefit from an intuitive design that makes insight easy to obtain so they can make informed decisions.
– They help convey your message – you’re in a better position to tell a coherent story. Applying design principles can also help accentuate your message. My colleague Kalina Ivanova has written an excellent series of blogs on Data Storytelling with Power BI.
– They encourage user adoption – if a report is useful to users and has a great look and feel then you’re winning.

In this blog, I’ll briefly cover the building blocks that make up a good Power BI dashboard. I then explore the stepping stones that will level up your dashboard and take it from good to great.

One area where I do have some disagreement is that the Z and F layouts are fine for text-heavy formats, but generally “text-heavy” and “dashboard” don’t go together very well. My preference is the notion of focal points (go about 3/4 of the way down, to the section entitled “Where We Look”), which works much better at describing eye behavior for image-heavy layouts. That aside, I like this post a lot.

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Good Practices for Naming Things in Power BI

Published 2020-06-30 by Kevin Feasel

Chris Webb shares some thoughts on the power of names:

What’s wrong with this picture? Look at the names:

– The tables and columns have the same names that they had in the data source, in this case a SQL Server database. Note the table name prefixes of “Dim” for dimensions and “Fact” for fact tables.
– The column and measure names either don’t have spaces or use underscores instead of spaces.
– What on earth does the measure name _PxSysF even mean?

Chris mentions that some of the ideas in the post may be controversial, but to be honest, I don’t think any of them are. The important thing here is to keep your audience in mind.

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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.

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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.

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