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Category: Power BI

Chart Style Controls

Wolfgang Strasser shows off a new feature in Power BI:

The theme documentation provides a list of available visual names, cardNames and property names.

At this point some further explanation is needed for the hierarchy within the theme definition:

  • visualName corresponds to available PBI visuals like treeMap, card, columnChart,…

  • styleName (as of today I am not sure whereto this corresponds to PBI Desktop language.. :-)) maybe someone can further explain this to me

  • cardName corresponds to the formatting card/option within Power BI Desktop. Attention here: the name in the theme JSON file is defined different than the User Interface name + do not forget case-sensitivity! (i.e.  general => General; categoryAxis => X-Axis, valueAxis => Y-Axis, ..). See the documentation for the rest of the mapping.

This is good news if it makes it easier for developers to write CVD-friendly reports.

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Sentiment Analysis In Power BI

Chris Webb has a new Power BI custom data connector:

I’m pleased to announce that I’ve published my first Power BI custom data connector on GitHub here:

https://github.com/cwebbbi/PowerBITextAnalytics

Basically, it acts as a wrapper for the Microsoft Cognitive Services Text Analytics API and  makes it extremely easy to do language detection, sentiment analysis and to extract key phrases from text when you are loading data into Power BI.

Read the whole thing, as Chris has a great demo of it.

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Drillthrough In Power BI Reports

Dustin Ryan shows off drillthrough actions in Power BI:

At some point this weekend, the Microsoft Power BI folks turned on the drillthrough feature in the Power BI service. This is the same drillthrough feature that demonstrated during day 1 of the Microsoft Data Insights Summit, which you can read about here. So I thought it’d be good to quickly walk through how you can set up the drill through action.

First, navigate to a report that you’ve already published to the Power BI service. This report will become the target of your drill-through action. Start editing the report and you’ll notice that on the right side there is a Drillthrough Filters section.

Read on for more.  At the moment, this is only available within the Power BI service, not in Desktop.

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Two Mobile Reporting Stories On The Microsoft Stack

Paul Turley talks about the two competing mobile stories on the Microsoft stack, namely SSRS with DataZen and Power BI:

This is the story of two products – or rather one product that is now a service and another product that is now a component of another product.  A few years ago, Microsoft began to formulate a mobile usability story among many fragmented tools.  They had a really good reporting product: SSRS, and they had a pretty good self-service BI capability offered as a bunch of Excel add-ins; namely: Power Pivot, Power Query and Power View – but it didn’t do mobile.  They bought Datazen which was a decent mobile reporting and dashboard tool, designed primarily for IT developers and semi-tech-savvy business pros to quickly create mobile dashboards using traditional data sources.  Datazen wasn’t really a self-service BI tool and wasn’t really designed to work with BI data in the true sense.  It was a good power user report tool but was young and needed to be refined and matured as a product.  Datazen became “Reporting Services Mobile Reports” and was integrated into the SSRS platform as a separate reporting experience with a separate design tool, optimized exclusively for use on mobile devices using platform-specific mobile phone and tablet apps.  Since initial roll-out, product development stalled and has not changed at all since it was released with SQL Server 2016 Enterprise Edition.

Paul gives us his current advice, as well as a hint at where things could be going.

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Loading Webpage Data Into Excel

Kerry Tyler has an interesting use of Excel:

Fortunately, there are some tools built right into Excel that make this a whole lot easier than scrolling through the list in your browser. Armed with nothing more than the URL to the CU’s KB article and Excel 2016 (or a few older versions) quick work can be made of generating custom filters for this data.

Here are the steps:

The same Power Query bits are available in Power BI, so check it out.

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Creating A Date Dimension In Power BI

Reza Rad has released part 1 of a series on creating date dimensions in Power BI:

When it comes to create the date (or calendar) dimension in Power BI, there is always a question: Should I create the dimension with Power Query or DAX? This is a very good question to ask. It means that you know that there are multiple ways of creating it. What is the difference? the answer is that for many scenarios these are similar. So, it might not be different to use Power Query or DAX for it. However, there is a big difference.

Power Query can fetch data from live web APIs. This functionality gives you the power to fetch public holidays live from an API. You cannot do this with DAX! Apart from this big difference, majority of other requirements can be done with both, you can write calculations in both M or DAX to get calendar columns as well as fiscal columns. In many scenarios public holidays plays an important role in analyzing data. You would like to know how the sales was in holidays compared to other holidays and etc.

There are a few more parts forthcoming, so stay tuned.

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Power BI Report Server August Preview

Aaron Nelson gives us a happy report:

Power BI Report Server August 2017 Preview is now available. Think of this a “v.Next” of Power BI Report Server [On-Premises], for all Data Sources.

Here’s an excerpt from the Power BI blog post from this weekend:

With this August 2017 preview, users can create Power BI reports in Power BI Desktop that connect to any data source, and publish their reports to Power BI Report Server. There’s no special configuration required to enable this functionality

Read on for more information and a link to download the latest preview.  It had me as soon as I read “all data sources.”

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Comparing Baselines Using Power BI

Melissa Connors shows how to take baseline data from SentryOne and visualize it within Power BI:

Using Power BI to connect to multiple baselines in SentryOne allows me to make fast comparisons. I previously translated baseline values into charts manually or through some Excel/SQL Server connections. See this post on data compression as an example. I wanted to compare performance between different compression levels (None, Row, and Page), and include the Average, Minimum, Maximum, and Standard Deviation values. Now, I have a standard template that looks better in Power BI. Once I create a baseline in my database, I have access to it in my charts. If you don’t have Power BI, you can use the query from this post in Excel or another reporting method for your comparisons.

Even if you don’t use SentryOne, the principles are generally applicable.

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