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Category: Power BI

Display Folder Nesting In Power BI

Chris Webb shows off a new feature to Power BI Desktop and notes a couple of issues with it:

The ability to add columns and measures to display folders in the new Modelling view is one of my favourite features of the November 2018 release of Power BI Desktop: it makes complex models a lot more user-friendly. Being an old-school SSAS developer, I immediately wondered if they worked in the same way that they do in SSAS – and the answer is yes and no.

The good news is that display folders can be nested.

Click through for a demo as well as the issues Chris spotted.

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The Value Of Power BI Dataflows

Matt Allington gets to the core benefits of Power BI Dataflows:

Dataflows are:

  1. An online service provided by Microsoft as part of Power BI (software as a service, or SaaS).

  2. In effect dataflows are an online data collection and storage tool.

    • Collection:  It uses Power Query to connect to the data at the source and transform that data as needed.
      • You will need to be able to access the data either through a cloud service (such as Dynamics 365) or to your PC/Network via a gateway.
      • You can also use Power Query to write queries from scratch, such as my Power BI calendar table.
    • Storage:  Dataflows then stores that data in a table in the cloud so it can be used directly inside PowerBI.com, but more importantly (from my view) directly from Power BI Desktop.
  3. Dataflows leverage the Power Query skills you have learnt (or are learning) using other tools (like Power BI Desktop, Power Query for Excel) allowing you to reuse those same skills in this online tool.

  4. Tables that are created as a result of the dataflow are stored in an Azure Data Lake.

    • If you don’t know what that is, don’t worry – I don’t understand it either.  The point is it doesn’t matter because it is all done automatically for you by the tool.
  5. Dataflows include the concept of the common data service (CDS) or common data model directly in the tool and you don’t have to know what it is, nor care.

    • If you don’t know what that is, don’t worry – it doesn’t matter now/yet.

    • This will become very important in the future as it will make the process of getting data out of complex databases (such as MS Dynamics 365) much easier in the future.

Click through for more detail as well as some good uses for Dataflows.

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Showing Forecasts With Actuals In Power BI

Alberto Ferrari shows us how we can incorporate actuals and forecasted values in the same Power BI visuals:

The Forecast measure in the demo model is quite an advanced piece of DAX code that would require a full article by itself. The curious reader will find more information on how to reallocate budget at different granularities in the video Budgeting with Power BI. In this article, we use the Forecast measure without detailed explanations; our goal is to explain how to compute the next measure: Remaining Forecast.

The Remaining Forecast measure must analyze the Sales table, finding the last day for which there are sales, and only then computing the forecasts.

Read the whole thing.

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Automated Testing With Power Query

Fred Kaffenberger walks us through query failure with Power Query:

I loved Nar’s post on Automated Testing using DAX. I especially like the rule of always including controls so that business readers can share responsibility for data quality. For my part, I sometimes use hidden pages in Power BI reports to assure myself of data quality. I also set alerts on testing dashboards in the Power BI Service to notify me if something is not right. Sometimes, however, a more proactive approach is needed. So, we’ll be doing automated testing with Power Query.

If the query can’t connect to the data source, it will fail. When this happens, the report in Power BI Service is stale, but accurate. I’m fine with thisIt can also happen that the query succeeds but is incomplete. In this case, the result is that the report is wrong. Why does this happen? It can happen because of an overtaxed transactional data source. The ERP or CRM or work order system just can’t deliver the amount of data. Maybe it’s linked SQL tables using ODBC. For whatever reason, the query succeeds, but data is missing. I’m NOT fine with this. The long-term solution is to move to a more reliable data source (data warehouse, anybody?). In the short run, refreshes must be stopped. Stale data is better than bad data.

Also check out the comments.

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Using Microsoft Flow To Find Power BI Data Sources In Use

Chris Webb continues his series on using Microsoft Flow to extend Power BI:

The problem with self-service BI is that you never quite know what your users are up to. For example, what data sources are they using? Are there hundreds of Excel files being used as data sources for reports that you don’t know about? If so, where are they? Could they and should they be replaced by a database or something else more robust? In this post I’ll show you how you can use Microsoft Flow and the Power BI REST API (see part 1 to find out how to create a Flow custom connector to call the Power BI API) to get the details of all the data sources used in all of the workspaces of your Power BI tenant.

I’ll admit that doing this turned out to be a bit trickier than I had expected. My plan was to use the GetDatasetsAsAdmin endpoint to get a list of all datasets, loop over each one and then call the (undocumented, but in the REST API’s Swagger file and therefore in my custom connector) GetDatsourcesAsAdmin endpoint to get the datasources in each dataset. Both these endpoints require administrative permissions to call, so I made sure my custom connector had the correct permissions (at least Tenant.Read.All – you can check this in the Azure Portal on the app you registered in Azure Active Directory) and I ran the Flow as a user with Power BI Admin permissions. But I kept getting 404 errors when requesting the data sources for certain datasets .

Chris explains why those 404s appear and what you can do about them.

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Editing ArcGIS Maps In Power BI

Jason Bonello shows us the types of changes we can make to ArcGIS maps in Power BI:

Map themes – This allows a change in the style for the map and once can choose from location only, heatmaps or clustering (the last two are only available for point layers, that is when you select Points in the Location Type). Through the clustering option, one could group individual location points into larger circular clusters that fall within a cluster radius – giving a high level view and then the ability to drill down into each region. If heatmaps are chosen any values in the Size or Color will be ignored and the tooltips will not be available.

Read the whole thing.

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Power BI: Choosing Between Default Or Custom Date Dimensions

Reza Rad looks at the default date dimension available in Power BI and compares it to what you can build yourself:

Oh yes! Of course like any other table structures in the Power BI in-memory based structure, every date table, consumes memory. But it would do the same even if you create your custom date dimension! Whenever you do the role-playing dimension scenario you are also consuming even more memory! The main difference is that Power BI default Date dimension will be created even if you do not want to do the date-based analysis on a date field! For example, even if you don’t use DueDate in your date-based analysis, still Power BI creates a date dimension for it. You cannot stop it for one field. You have to either stop the default creation of the Date dimension for the entire model or use it for the entire model, you cannot customize it per field. But with the custom date dimension, you can.

Reza does a good job of giving us the trade-offs between these two and explaining when we should use each.

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Building Custom R Visuals In Power BI

Brad Lewellyn shows us how to create custom R visuals within Power BI:

Over the last few posts, we’ve shown how to use custom R visuals built by others.  Today, we’re going to build our own using the Custom R Visual available in Power BI Desktop.  If you haven’t read the second post in this series, Getting Started with R Scripts, it is highly recommended you do so now, as it provides necessary context for how to link Power BI to your local R ISE.

In the previous post, we created a bunch of log-transformed measures to find good predictors for Revenue.  We’re going to use these same measures today to create a basic linear regression model to predict Revenue.  If you want to follow along, the dataset can be found here.  Here’s the custom DAX we used to create the necessary measures.

Click through for the example.

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Tying The Power BI Threads Together

Eugene Meidinger has a corkboard with a bunch of pushpins connecting photographs and newspaper articles together with string:

Part of that announcement was them talking about the Common Data Service. When I first heard about CDS months ago, I was again confused. It sounded like some weird semantic layer for the data in Dynamics CRM. Maybe useful if your data lives in Dynamics 365, otherwise who the heck cares.

Oooooh boy was I wrong. Microsoft is aiming for something much, much more ambitious than an awkward pseudo-database layer for people who don’t like SQL. They are aiming for a common shape for all of your business data. They want to want to create a lingua franca for all of your business data, no matter where it is. Especially if it’s hiding in Salesforce.

Now, do I expect them to succeed? I’m not sure. I’ve learned the hard way that every business is a unique snowflake, even two business in exact same industry. But if anyone can do it, Microsoft has a good shot. They’ve been buying up CRM / ERP solutions for decades.

There’s some good stuff in here, including the realization that Power BI is not strictly intended for database developers.

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Creating A Panel For Slicers In Power BI

Matt Allington shows us how to create a collapsable panel in Power BI:

There is nothing worse than having a Power BI report that has 50% of the space taken up with slicers.  When this happens, you only get half the page to visualise the actual data.  But on the flip side, if you don’t have the slicers it can be harder for the report users to filter the data they want to see.  Many users don’t like using the built in filter pane on the right hand side.  All is not lost – there is a great way that you can have the best of both worlds by creating a collapsible slicer pane that you can show and hide on demand.

Now I didn’t invent this concept – I learnt it from looking at what others have done, such as Amanda Cofsky, Miguel Myers, Mike and Seth from http://powerbi.tips and also Adam and Patrick from GuyInACube.  There are lots of great resources out there to learn tricks like this, so you should check those out.

You can see one simple interpretation of this solution below. The user can hide and collapse the slicer pane by using the arrow keys (#1 and #2 below).

Click through for the demo.

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